Population and Housing Census of Myanmar, 2014 DDI_MMR_2014_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

 IPUMS April 2, 2025 IPUMS, 50 Willey Hall, 225 - 19th Avenue South, Minneapolis, MN 55455 Organization for Economic Co-operation and Development, Development Co-operation Directorate JADE#:60525;MEHLB(2010)12 IPUMS Version 7.6 October 2025 : NEW FEATURES. --NO "new features" listed in Revision History NEW SAMPLES. --Six new census samples for Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017) were added to the data series. All census samples extend pre-existing series for those countries. --91 quarterly labor force surveys from the Philippines (1997 - 2019) were added to IPUMS. SUPPLEMENTAL DATA. --No "supplemental data" listed in revision history NEW VARIABLES. --New spatially harmonized birthplace and previous-residence variables are available for samples in this data release. More information is available here (https://international.ipums.org/international/geo_mig.shtml). --Users should note that many older migration and birthplace variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. For birthplace variables refer to this table (https://international.ipums.org/international/resources/misc_docs/migCrosswalk_names.pdf). EDITED SAMPLES. --For the Zambia 2000 sample, an error in the household breaks was corrected, resulting in the creation of 1,988 new households (1% increase) that were previously combined with other households. The person records included in the sample did not change. Due to an inconsistency in the original file, no household-level information other than geographic location is available for these newly identified households, necessitating the addition of "unknown" values for this sample to the following variables: BEDROOMS, ELECTRIC, FLOOR, FUELCOOK, FUELHEAT, OWNERSHIP, PHONE, RADIO, REFRIG, ROOMS, SEWAGE, TRASH, WATSRC, TV, TOILET, GQ, ROOF, WATSUP, BIKE, MOTORCYCLE, KITCHEN, GQTYPE, AUTOS, and WALL. EDITED VARIABLES. --For the 1998 and 2008 Malawi samples, the family interrelationship pointer variables MOMLOC and POPLOC were modified to allow a "Spouse/partner" of the household head to be linked as a parent to an "Other relative", because the enumeration instructions specify that adopted and stepchildren were categorized as "Other relative". These samples are now consistent with the links made in the newly released 2018 Malawi sample, which had the same enumeration instructions for adopted and stepchildren. --In the samples for Côte d'Ivoire 1988 and 1998, Rwanda 1991 and 2002, Togo 1960 and 2010, and South Africa 2001, for the harmonized variable POLYGAM, persons in consensual unions were previously coded as "No, in monogamous union". Because there was no response option in these samples for polygamous consensual unions, it is more appropriate to treat these cases as not-in-universe, so they have been recoded to "NIU (not in universe)". --MARST has been edited for Honduras 1974 to reclassify the source variable responses "married, wife lives separately" and "consensual union, companion lives separately" as separations. The documentation suggests that "separately" actually indicates a relationship separation and not an absent spouse or companion. Other minor edits were implemented for MARST for Mozambique 1997 and 2007. --In the Mozambique 1997 sample, an error was corrected that recoded persons with a relationship of "Unknown" in the source data to "Other relative or non-relative" (6000) in the harmonized variable RELATE. These persons are now coded as "Not Stated/Unknown" (9999). --In the Malawi 1987, 1998, and 2008 samples, for variable WATSUP, a programming error was corrected such that any households who reported having piped water in either the wet or the dry season are classified as having access to piped water. This programming was also applied to the newly released 2018 sample. --The NATIVITY variable has been edited in the Chile 2017 sample to correct a programming error that mistakenly classified as foreign-born about 20 thousand person records that were actually native-born. --The MIGRATE5 variable has been edited in the Chile 2017 sample, given a programming error that classified most migrants as having changed their major geographic unit. The MIGRATE5 variable for the Chile 1982 and 1992 samples has been edited to use spatially harmonized geographic units to calculate migration status. --In the 1989, 1999, and 2009 Kenya samples, households who indicated that their lighting type or fuel was "Solar" were recoded from "No" to "Yes" in ELECTRIC, based on secondary sources documenting the spread of home solar energy systems in Kenya beginning in the mid-1980s. In the 1989 and 1999 Kenya samples, programming was removed that previously recoded households that reported using electricity as their main cooking fuel to "Yes" in the access to electricity variable ELECTRIC, making it more consistent across samples. Other minor edits were implemented for ELECTRIC in Botswana 2011, Ethiopia 1984 and 1994, Mongolia 1989, Mozambique 2007. --Some samples in DISCARE classified responses indicating "some" difficulty into "yes". These cases were revised to consistently include in "yes" only responses indicating "a lot of difficulty" or "cannot do at all". --Some codes were improperly labeled for municipalities in Honduras 1961 and 1974, which affect variables on place of residence, birthplace, and previous residence. Population and Housing Census of Myanmar, 2014 - IPUMS Subset PHC mm2014a (IPUMS Harmonized Subset) MMR_2014_PHC_v01_M_v7.6_A_IPUMS Department of Population, Ministry of Immigration and Population IPUMS (c) Copyright 2014, Department of Population, Ministry of Immigration and Population and Minnesota Population Center Department of Population, Ministry of Immigration and Population Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Nativity and Birthplace Variables -- PERSON Utilities Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Work Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Geography: F-N Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Migration: F-N Variables -- PERSON Household Economic Variables -- HOUSEHOLD Technical Person Variables -- PERSON Technical Household Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Disability Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Education Variables -- PERSON Technical Person Variables -- PERSON Household Economic Variables -- HOUSEHOLD Geography: F-N Variables -- HOUSEHOLD Demographic Variables -- PERSON Other Person Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON Fertility and Mortality Variables -- PERSON March 29, 2014 March 29 to April 10, 2014 Myanmar Township Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: A dwelling unit includes a building or structure in which people are living, whether or not it is a "conventional dwelling." Non-conventional dwellings, such as mobile units (trailers, vans, tents, boats), semi-permanent structures (shacks) or improvised units (makeshift shelter) should be enumerated. - Households: A household refers to one or more persons who usually share their living quarters (single quarter or compound) and share their meals. In common usage it might be said that a household consists of “all persons living and eating together or eating from the same cooking-pot”. They may be residing in several structures within a compound like in the rural areas. - Group quarters: Coolective households are groups of people live together but cannot be said to belong to a conventional “ordinary” household. Examples are;- old-people’s homes, orphanages, hospitals and rehabilitation centers, including children’s hospitals and psychiatric hospitals, boarding schools, hotels, hostels and inns, institutions for people with disabilities, prisons and other penal institutions, religious centers - including monasteries and convents, camps for workers, military and police barracks, etc. All persons who spent the census night in Myanmar. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Myanmar 2014 MICRODATA SOURCE: Department of Population, Ministry of Immigration and Population SAMPLE SIZE (person records): 5032818. SAMPLE DESIGN: Systematic sample of enumerated households, stratified by geographic unit, drawn by the Department of Population, Ministry of Immigration and Population. Face-to-face [f2f] Separate enumeration form for each dwelling de facto, CENSUS DAY: March 29, 2014 Weights calculated by the Department of Population, Ministry of Immigration and Population. IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Department of Population, Ministry of Immigration and Population Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee, and Nate Merrill. Integrated Public Use Microdata Series, International: Version 7.6 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D020.V7.6 Researchers should also acknowledge the statistical agency that originally produced the data: Myanmar, Department of Population, Ministry of Immigration and Population. Population and Housing Census of Myanmar, 2014 The licensing agreement for use of IPUMS International data requires that users supply IPUMS International with the title and full citation for any publications, research reports, or educational materials making use of the data or documentation. Copies of such materials are also gratefully received at ipums@umn.edu. Printed matter should be sent to: IPUMS International Minnesota Population Center University of Minnesota 50 Willey Hall 225 19th Avenue South Minneapolis, MN 55455 An adapted version of the dataset, harmonized for international comparability, is available from IPUMS International (https://international.ipums.org/international/) under the following conditions: IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. User-provided description: DOI:10.18128/D020.V7.6 Extract for mm2014a, 2025 MMR2014_PHC-H-H.dat Household records 1,237,712 ascii Minnesota Population Center Version 7.5, IPUMS sample MMR2014_PHC-P-H.dat Person records 5032818 ascii Minnesota Population Center Version 7.5, IPUMS sample Record type RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. H Household P Person Technical Household Variables -- HOUSEHOLD Country COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Côte d'Ivoire 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe Technical Household Variables -- HOUSEHOLD Year YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 Technical Household Variables -- HOUSEHOLD IPUMS sample identifier SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 340201301 Honduras 2013 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Côte d'Ivoire 1988 384199801 Côte d'Ivoire 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 404201901 Kenya 2019 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 454201801 Malawi 2018 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 496201001 Mongolia 2010 496202001 Mongolia 2020 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 508201701 Mozambique 2017 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199721 Philippines 1997 Q1 LFS 608199722 Philippines 1997 Q2 LFS 608199723 Philippines 1997 Q3 LFS 608199724 Philippines 1997 Q4 LFS 608199821 Philippines 1998 Q1 LFS 608199822 Philippines 1998 Q2 LFS 608199823 Philippines 1998 Q3 LFS 608199824 Philippines 1998 Q4 LFS 608199921 Philippines 1999 Q1 LFS 608199922 Philippines 1999 Q2 LFS 608199923 Philippines 1999 Q3 LFS 608199924 Philippines 1999 Q4 LFS 608200021 Philippines 2000 Q1 LFS 608200022 Philippines 2000 Q2 LFS 608200023 Philippines 2000 Q3 LFS 608200024 Philippines 2000 Q4 LFS 608200121 Philippines 2001 Q1 LFS 608200122 Philippines 2001 Q2 LFS 608200123 Philippines 2001 Q3 LFS 608200124 Philippines 2001 Q4 LFS 608200221 Philippines 2002 Q1 LFS 608200222 Philippines 2002 Q2 LFS 608200223 Philippines 2002 Q3 LFS 608200224 Philippines 2002 Q4 LFS 608200321 Philippines 2003 Q1 LFS 608200322 Philippines 2003 Q2 LFS 608200323 Philippines 2003 Q3 LFS 608200324 Philippines 2003 Q4 LFS 608200421 Philippines 2004 Q1 LFS 608200422 Philippines 2004 Q2 LFS 608200423 Philippines 2004 Q3 LFS 608200424 Philippines 2004 Q4 LFS 608200521 Philippines 2005 Q1 LFS 608200522 Philippines 2005 Q2 LFS 608200523 Philippines 2005 Q3 LFS 608200524 Philippines 2005 Q4 LFS 608200621 Philippines 2006 Q1 LFS 608200622 Philippines 2006 Q2 LFS 608200623 Philippines 2006 Q3 LFS 608200624 Philippines 2006 Q4 LFS 608200721 Philippines 2007 Q1 LFS 608200722 Philippines 2007 Q2 LFS 608200723 Philippines 2007 Q3 LFS 608200724 Philippines 2007 Q4 LFS 608200821 Philippines 2008 Q1 LFS 608200822 Philippines 2008 Q2 LFS 608200823 Philippines 2008 Q3 LFS 608200824 Philippines 2008 Q4 LFS 608200921 Philippines 2009 Q1 LFS 608200922 Philippines 2009 Q2 LFS 608200923 Philippines 2009 Q3 LFS 608200924 Philippines 2009 Q4 LFS 608201021 Philippines 2010 Q1 LFS 608201022 Philippines 2010 Q2 LFS 608201023 Philippines 2010 Q3 LFS 608201024 Philippines 2010 Q4 LFS 608201121 Philippines 2011 Q1 LFS 608201122 Philippines 2011 Q2 LFS 608201123 Philippines 2011 Q3 LFS 608201124 Philippines 2011 Q4 LFS 608201221 Philippines 2012 Q1 LFS 608201222 Philippines 2012 Q2 LFS 608201223 Philippines 2012 Q3 LFS 608201224 Philippines 2012 Q4 LFS 608201321 Philippines 2013 Q1 LFS 608201322 Philippines 2013 Q2 LFS 608201323 Philippines 2013 Q3 LFS 608201324 Philippines 2013 Q4 LFS 608201421 Philippines 2014 Q1 LFS 608201422 Philippines 2014 Q2 LFS 608201423 Philippines 2014 Q3 LFS 608201424 Philippines 2014 Q4 LFS 608201521 Philippines 2015 Q1 LFS 608201522 Philippines 2015 Q2 LFS 608201523 Philippines 2015 Q3 LFS 608201524 Philippines 2015 Q4 LFS 608201621 Philippines 2016 Q1 LFS 608201622 Philippines 2016 Q2 LFS 608201623 Philippines 2016 Q3 LFS 608201624 Philippines 2016 Q4 LFS 608201721 Philippines 2017 Q1 LFS 608201722 Philippines 2017 Q2 LFS 608201723 Philippines 2017 Q3 LFS 608201724 Philippines 2017 Q4 LFS 608201821 Philippines 2018 Q1 LFS 608201822 Philippines 2018 Q2 LFS 608201823 Philippines 2018 Q3 LFS 608201824 Philippines 2018 Q4 LFS 608201921 Philippines 2019 Q1 LFS 608201922 Philippines 2019 Q2 LFS 608201923 Philippines 2019 Q3 LFS 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 Technical Household Variables -- HOUSEHOLD Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. Technical Household Variables -- HOUSEHOLD Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. Technical Household Variables -- HOUSEHOLD Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Household Variables -- HOUSEHOLD Subsample number SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample Technical Household Variables -- HOUSEHOLD Group quarters (collective dwelling) status GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified Group Quarters Variables -- HOUSEHOLD Number of unrelated persons UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each country. 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia Geography: Global Variables -- HOUSEHOLD 1st subnational geographic level, world [consistent boundaries over time] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. Geography: Global Variables -- HOUSEHOLD 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO1 is an 8-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO1 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Myanmar, State or region 2014 [Level 1; consistent boundaries, GIS] GEO1_MM identifies the household's state within Myanmar in all sample years. States are the first level administrative units of the country. GEO1_MM is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_MM can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Myanmar can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 104001 Kachin 104002 Kayah 104003 Kayin 104004 Chin 104005 Sagaing 104006 Tanintharyi 104007 Bago 104008 Magway 104009 Mandalay 104010 Mon 104011 Rakhine 104012 Yangon 104013 Shan 104014 Ayeyawady 104015 Nay Pyi Taw Geography: F-N Variables -- HOUSEHOLD Myanmar, State or region 2014 [Level 1, GIS] GEO1_MM2014 identifies the household's state within Myanmar in 2014. States are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_MM2014 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Myanmar can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001 Kachin 002 Kayah 003 Kayin 004 Chin 005 Sagaing 006 Tanintharyi 007 Bago 008 Magway 009 Mandalay 010 Mon 011 Rakhine 012 Yangon 013 Shan 014 Ayeyawady 015 Nay Pyi Taw Geography: F-N Variables -- HOUSEHOLD Myanmar, District 2014 [Level 2; consistent boundaries, GIS] GEO2_MM identifies the household's district within Myanmar in all sample years. Districts are the second level administrative units of the country, after states. GEO2_MM is spatially harmonized accounting for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO2_MM can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Myanmar can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 104001001 Myitkyina 104001002 Mohnyin 104001003 Bhamo 104001004 Putao 104002001 Loikaw 104002002 Bawlakhe 104003001 Hpa-An 104003002 Pharpon 104003003 Myawady 104003004 Kawkareik 104004001 Haka 104004002 Falam 104004003 Mindat 104005001 Sagaing 104005002 Shwebo 104005003 Monywa 104005004 Katha 104005005 Kalay 104005006 Tamu 104005007 Mawlaik 104005008 Hkamti 104005009 Yinmarpin 104006001 Dawei 104006002 Myeik 104006003 Kawthoung 104007001 Bago 104007002 Toungoo 104007003 Pyay 104007004 Thayawady 104008001 Magway 104008002 Minbu 104008003 Thayet 104008004 Pakokku 104008005 Gangaw 104009001 Mandalay 104009002 Pyin Oo Lwin 104009003 Kyaukse 104009004 Myingyan 104009005 Nyaung U 104009006 Yame`Thin 104009007 Meiktila 104010001 Mawlamyine 104010002 Thaton 104011001 Sittway 104011002 Myauk U 104011003 Maungtaw 104011004 Kyaukpyu 104011005 Thandwe 104012001 North Yangon 104012002 East Yangon 104012003 South Yangon 104012004 West Yangon 104013001 Taunggyi 104013002 Loilin 104013003 Linkhe` 104013004 Lashio 104013005 Muse 104013006 Kyaukme 104013007 Kunlon 104013008 Laukine 104013009 Hopan 104013010 Makman 104013011 Kengtung 104013012 Minesat 104013013 Tachileik 104013014 Minephyat 104014001 Pathein 104014002 Phyapon 104014003 Maubin 104014004 Myaungmya 104014005 Labutta 104014006 Hinthada 104015001 Ottara (North) 104015002 Dekkhina (South) Geography: F-N Variables -- HOUSEHOLD Myanmar, District 2014 [Level 2, GIS] GEO2_MM2014 identifies the household's district within Myanmar in 2014. Districts are the second level administrative units of the country, after states. A GIS map (in shapefile format), corresponding to GEO2_MM2014 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Myanmar can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001001 Myitkyina 001002 Mohnyin 001003 Bhamo 001004 Putao 002001 Loikaw 002002 Bawlakhe 003001 Hpa-An 003002 Pharpon 003003 Myawady 003004 Kawkareik 004001 Haka 004002 Falam 004003 Mindat 005001 Sagaing 005002 Shwebo 005003 Monywa 005004 Katha 005005 Kalay 005006 Tamu 005007 Mawlaik 005008 Hkamti 005009 Yinmarpin 006001 Dawei 006002 Myeik 006003 Kawthoung 007001 Bago 007002 Toungoo 007003 Pyay 007004 Thayawady 008001 Magway 008002 Minbu 008003 Thayet 008004 Pakokku 008005 Gangaw 009001 Mandalay 009002 Pyin Oo Lwin 009003 Kyaukse 009004 Myingyan 009005 Nyaung U 009006 Yame`Thin 009007 Meiktila 010001 Mawlamyine 010002 Thaton 011001 Sittway 011002 Myauk U 011003 Maungtaw 011004 Kyaukpyu 011005 Thandwe 012001 North Yangon 012002 East Yangon 012003 South Yangon 012004 West Yangon 013001 Taunggyi 013002 Loilin 013003 Linkhe` 013004 Lashio 013005 Muse 013006 Kyaukme 013007 Kunlon 013008 Laukine 013009 Hopan 013010 Makman 013011 Kengtung 013012 Minesat 013013 Tachileik 013014 Minephyat 014001 Pathein 014002 Phyapon 014003 Maubin 014004 Myaungmya 014005 Labutta 014006 Hinthada 015001 Ottara (North) 015002 Dekkhina (South) Geography: F-N Variables -- HOUSEHOLD Myanmar, Township 2014 [Level 3, GIS] GEO3_MM2014 identifies the household's township within Myanmar in 2014. Townships are the third level administrative units of the country, after districts and states. A GIS map (in shapefile format), corresponding to GEO3_MM2014 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Myanmar can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001001001 Myitkyina, Hsinbo 001001002 Waingmaw, Kanpaikti, Hsadone 001001004 Tanaing, Shinbwayyan 001001005 Chiphwe, Hsotlaw, Ingyanyan, Panwa 001002001 Mohnyin 001002002 Mogaung 001002003 Phakant, Kamine 001002051 Hopin 001003001 Bhamo 001003002 Shwegu, Myohla 001003003 Momauk, Lwe'Ge', Dotphoneyan 001003004 Mansi 001004001 Putao, Sumprabum 001004004 Khaunglanphoo, Machanbaw, Naungmoon, Pannandin 002001001 Loikaw, Shardaw 002001002 Dimawso 002001003 Phruso 002002002 Parsaung, Bawlakhe, Meisi, Ywathit 003001001 Hpa-an 003001002 Hlaingbwe 003001003 Thandaunggyi, Bawgali 003001051 Paingkyon 003001052 Shan Ywathit 003001053 Leiktho 003002001 Pharpon, Kamamaung 003003001 Myawady, Sugali, Wawlaymyaing 003004001 Kawkareik 003004002 Kyarinseikkyi 003004051 Payarthonezu 003004052 Kyaidon 004001001 HaKa 004001002 Thantlang 004002001 Falam 004002002 Tedim, Rihkhuadal 004002003 Tonzaung, Cikha 004003001 Mindat 004003002 Matupi, Reazu 004003003 Kanpalet 004003004 Paletwa 004003052 Sami 005001001 Sagaing 005001002 Myinmu 005001003 Myaung 005002001 Shwebo 005002002 KhinU 005002003 Wetlet 005002004 Kambalu 005002005 Kyunhla 005002006 YeU 005002007 Depayin 005002008 Tasei 005002051 Kyaukmyaung 005003001 Monywa 005003002 Butalin 005003003 Ayartaw 005003004 ChaungOo 005004001 Katha 005004002 Indaw 005004003 Tigyaing 005004004 Banmauk 005004005 Kawlin 005004006 Wuntho 005004007 Pinlebu 005005001 Kalay 005005002 Kalewa 005005003 Mingin 005006001 Tamu, Myothit 005006052 Khampat 005007001 Mawlaik 005007002 Phaungpyin 005008001 Hkamti 005008002 Homalin, Leshi, Mobaingluk, Sonemara 005008004 Lahe, Htanparkway 005008005 Nanyun, Pansaung 005008055 Donhee 005009001 Yinmarpin 005009002 Salingyi 005009003 Palae 005009004 Kani 006001001 Dawei 006001002 Lounglon 006001003 Thayetchaung 006001004 Yebyu 006001051 Myitta 006001052 Kaleinaung 006002001 Myeik 006002002 Kyunsu 006002003 Palaw 006002004 Tanintharyi 006002051 Palauk 006003001 Kawthoung 006003002 Bokepyin, Karathuri, Pyigyimandaing 006003051 Khamaukkyi 007001001 Bago 007001002 Tanatpin 007001003 Kawa 007001004 Waw 007001005 Nyaunglebin 007001006 Kyauktaga 007001007 DaikU 007001008 Shwegyin 007002001 Toungoo 007002002 Yaedashe 007002003 Kyaukkyi 007002004 Pyu 007002005 Oatwin 007002006 Htantapin 007003001 Pyay 007003002 Paukkhaung 007003003 Padaung 007003004 Paunde 007003005 Thegon 007003006 Shwedaung 007004001 Thayawady 007004002 Letpadan 007004003 Minhla 007004004 Okpo 007004005 Zigon 007004006 Nattalin 007004007 Monyo 007004008 Gyobingauk 008001001 Magway 008001002 Yenangyoung 008001003 Chauk 008001004 Taungdwingyi 008001005 Myothit 008001006 Natmauk 008002001 Minbu 008002002 PwintPhyu 008002003 Ngape 008002004 Salin 008002005 Saytottara 008003001 Thayet 008003002 Minhla 008003003 Mindon 008003004 Kamma 008003005 Aunglan 008003006 Sinpaungwe` 008004001 Pakokku 008004002 Yesagyo 008004003 Myaing 008004004 Pauk 008004005 Seikphyu 008005001 Gangaw 008005002 Htilin 008005003 Saw 008005051 Kyaukhtu 009001001 Aungmyetharzan 009001002 Chanayetharzan 009001003 Mahaaungmye 009001004 Chanmyatharzi 009001005 Pyigyidagun 009001006 Amarapura 009001007 Patheingyi 009002001 PyinOoLwin 009002002 Madaya 009002003 Sinku 009002004 Mogok 009002005 Thabeikkyin 009002051 Tagaung 009003001 Kyaukse 009003002 Singaing 009003003 Myitthar 009003004 TadaU 009004001 Myingyan 009004002 Taungtha 009004003 Natogyi 009004004 Kyaukpadaung 009004005 Ngazun 009005001 NyaungU 009005051 Ngathayauk 009006001 Yame`thin 009006002 Pyawbwe 009007001 Meiktila 009007002 Mahlaing 009007003 Thazi 009007004 Wundwin 010001001 Mawlamyine 010001002 Kyaikemaraw 010001003 Chaungzon 010001004 Thanbyuzayat 010001005 Mudon 010001006 Ye 010001051 Lamine 010001052 Khawzar 010002001 Thaton 010002002 Paung 010002003 Kyaikto 010002004 Bilin 011001001 Sittway 011001002 Ponnagyun 011001003 Pauktaw 011001004 Yathedaung 011002001 MyaukU 011002002 Kyauktaw 011002003 Minbya 011002004 Myebon 011003001 Maungtaw, Taungpyoletwe 011003002 Buthidaung 011004001 Kyaukpyu 011004002 Mannaung 011004003 Yanbye 011004004 An 011005001 Thandwe 011005002 Toungup 011005003 Gwa 011005051 Maei 011005052 Kyeintali 012001001 Insein 012001002 Mingaladon 012001003 Hmawby 012001004 Hlegu 012001005 Taikkyi 012001006 Htantabin 012001007 Shwepyitha 012001008 Hlinethaya 012002001 Thingangyun 012002002 Yankin 012002003 South Okkalapa 012002004 North Okkalapa 012002005 Thakayta 012002006 Dawbon 012002007 Tamway 012002008 Pazuntaung 012002009 Botahtaung 012002010 Dagon Myothit (South) 012002011 Dagon Myothit (North) 012002012 Dagon Myothit (East) 012002013 Dagon Myothit (Seikkan) 012002014 MingalaTaungnyunt 012003001 Thanlyin 012003002 Kyauktan 012003003 Thongwa 012003004 Khayan 012003005 Twantay 012003006 Kawhmu 012003007 Kungyangon, Cocogyun 012003008 Dala 012003009 Seikkyi/Khanaungto 012003051 Tada 012004001 Kyauktada 012004002 Pabedan 012004003 Lanmadaw 012004004 Latha 012004005 Ahlon, Seikkan 012004006 Kyimyindine 012004007 Sangyoung 012004008 Hline 012004009 Kamayut 012004010 Mayangon 012004011 Dagon 012004012 Bahan 013001001 Taunggyi 013001002 Nyaungshwe 013001003 Hopon 013001004 Hsihseng 013001005 Kalaw 013001006 Pindaya 013001007 Ywarngan 013001008 Yatsauk 013001009 Pinlaung 013001010 Phekon 013001051 Kyauktalongyi 013001052 Indaw 013001053 Naungtayar 013002001 Loilem 013002002 Le`char 013002003 Nanhsam (South) 013002004 Kunhing, Karli 013002005 Kehsi 013002006 Mongkai 013002007 Mineshu 013002051 Panglong 013002052 Kholan 013002054 Minenaung 013002055 Minesan 013003001 Linkhe`, Homane 013003002 Mone`, Kengtaung 013003003 Maukme` 013003004 Minepan 013004001 Lashio 013004002 Theinni 013004003 Mineye` 013004004 Tantyan 013005001 MuSe 013005002 Namkham, Manhero 013005003 Kukai 013005051 Monekoe 013005053 Pansai 013005054 Tamoenye 013006001 Kyaukme, Minengaw 013006002 Naungkhio 013006003 Hsipaw 013006004 Namtu 013006005 Namsan (North) 013006006 Momeik 013006007 Mabane 013006008 Manton 013006052 Minelon 013007001 Kunlon 013008001 Laukine, Chinshwehaw 013008002 Kongyan 013008052 Mawhtike 013009001 Hopan, Panlon 013009002 Minemaw 013009003 Panwine 013010002 PanSan(PanKham), Makman, Mankan 013010003 Naphang 013011001 Kengtung 013011002 Minekat 013011003 Mineyan 013011004 Minelar 013011051 Mine Pauk 013012001 Minepyin, Tontar 013012002 Minesat, Minekoke 013012003 Minetung, Monehta 013012053 Ponparkyin 013013001 Tachileik, Talay, Kenglat 013014001 Minephyat 013014002 Mineyaung 013014051 Mineyu 014001001 Kangyidaunt 014001002 Kyaungon 014001003 Kyonpyaw 014001004 Ngaputaw 014001005 Pathein 014001006 Yekyi 014001007 Thapaung 014001051 Ngayokaung 014001052 Hainggyikyun 014001053 Shwethaungyan 014001054 Ngwehsaung 014001055 Ngathaingchaung 014002001 Kyaiklatt 014002002 Daydaye 014002003 Phyapon 014002004 Bogale 014002051 Ahmar 014003001 Nyaungdon 014003002 Danubyu 014003003 Pantanaw 014003004 Maubin 014004001 Myaungmya 014004002 Wakema 014004003 Einme 014005001 Mawlamyinegyun 014005002 Labutta 014005051 Pyinsalu 014006001 Kyangin 014006002 Zalun 014006003 Myanaung 014006004 Laymyethna 014006005 Hinthada 014006006 Ingapu 015001001 Tatkon 015001002 Zeyarthiri 015001003 Ottarathiri 015001004 Pobbathiri 015002001 Pyinmana 015002002 Lewe 015002003 Zabuthiri 015002004 Dekkhinathiri Geography: F-N Variables -- HOUSEHOLD DHS-IPUMS-I Myanmar regions, 2014-2015 [consistent boundaries, GIS] DHS_IPUMSI_MM provides geographic codes for Myanmar that match those in the DHS and IPUMS-International databases. This variable can be used to link contextual area data from IPUMS-DHS to IPUMS-International or vice versa. The codes in DHS_IPUMSI_MM indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Liberia can be downloaded here. 01 Kachin 02 Kayah 03 Kayin 04 Chin 05 Sagaing 06 Taninthayi 07 Bago 08 Magway 09 Mandalay 10 Mon 11 Rakhine 12 Yangon 13 Shan 14 Ayeyarwaddy 15 NayPyitaw Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Ownership of dwelling [general version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 0 NIU (not in universe) 1 Owned 2 Not owned 9 Unknown Household Economic Variables -- HOUSEHOLD Ownership of dwelling [detailed version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 000 NIU (not in universe) 100 Owned 110 Owned, already paid 120 Owned, still paying 130 Owned, constructed 140 Owned, inherited 190 Owned, other 191 Owned, house 192 Owned, condominium 193 Apartment proprietor 194 Shared ownership 200 Not owned 210 Renting, not specified 211 Renting, government 212 Renting, local authority 213 Renting, parastatal 214 Renting, private 215 Renting, private company 216 Renting, individual 217 Renting, collective 218 Renting, joint state and individual 219 Renting, public subsidized 220 Renting, private subsidized 221 Renting, co-tenant 222 Renting, relative of tenant 223 Renting, cooperative 224 Renting, with a job or business 225 Renting, loan-backed habitation 226 Renting, mixed contract 227 Furnished dwelling 228 Sharecropping 230 Subletting 231 Rent to own 239 Renting, other 240 Occupied de facto/squatting 250 Free/usufruct (no cash rent) 251 Free, provided by employer 252 Free, without work or services 253 Free, provided by family or friend 254 Free, private 255 Free, public 256 Free, condemned 257 Free, other 260 Endowment, Waqf (Egypt historical) 290 Not owned, other 999 Unknown Household Economic Variables -- HOUSEHOLD Electricity ELECTRIC indicates whether the household had access to electricity. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Utilities Variables -- HOUSEHOLD Water supply WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. 00 NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown Utilities Variables -- HOUSEHOLD Cooking fuel FUELCOOK indicates the predominant type of fuel or energy used for cooking. 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing Utilities Variables -- HOUSEHOLD Telephone availability PHONE indicates the availability of a telephone in the dwelling. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Utilities Variables -- HOUSEHOLD Cellular phone availability CELL indicates the availability of a cellular phone in the household. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Utilities Variables -- HOUSEHOLD Internet access INTERNET indicates whether or not the household had an internet connection. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown Utilities Variables -- HOUSEHOLD Automobiles available AUTOS records whether a member of the household owned or had use of a vehicle and, in many samples, the number of such vehicles. 0 No autos 1 1 auto 2 2 autos 3 3 autos 4 4 autos 5 5 autos 6 6+ autos 7 Have auto, number unspecified 8 Unknown 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Computer COMPUTER indicates whether the household had a personal computer. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Television set TV indicates whether the household had a television. 00 NIU (not in universe) 10 No 20 Yes, color or black-and-white not specified 21 1 television 22 2 televisions 23 3 televisions 24 4 televisions 25 5 televisions 26 6 televisions 27 7 televisions 28 8 televisions 29 9+ televisions 30 Yes, at least one color tv 31 1 color tv 32 2 color tvs 33 3+ televisions 40 Yes, black-and-white only 41 1 black-white tv 42 2 black-white tvs 43 3+ black-white tvs 99 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Radio in household RADIO indicates whether the household had a radio. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Toilet TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Floor material FLOOR indicates the dwelling's predominant flooring material. 000 NIU (not in universe) 100 None/unfinished (earth) 110 Sand 120 Dung 200 Finished 201 Cement, tile, or brick 202 Cement 203 Concrete 204 Cement screed 205 Ceramic tile 206 Paving stone, cement tile 207 Stone 208 Brick 209 Brick or stone 210 Brick or cement 211 Block 212 Terrazzo 213 Wood 214 Palm, bamboo 215 Parquet 216 Parquet, tile, vinyl 217 Parquet, tile, marble 218 Ceramic, marble, granite 219 Ceramic, marble, tile, or vinyl 220 Marble 221 Mosaic 222 Tile 223 Tile, linoleum, ceramic, etc 224 Tile, cement 225 Tile, stone 226 Tile, stone, brick 227 Tile, stone, vinyl, brick 228 Tile, vinyl, brick 229 Tile, vinyl 230 Vinyl, linoleum, etc 231 Asphalt sheet, vinyl, etc 232 Synthetic, plastic 233 Cane 234 Carpet, rug 235 Scrap material 236 Other finished, n.e.c. 999 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Wall or building material This variable indicates the primary material used in the construction of the dwelling, particularly the dwelling's exterior walls. 000 NIU (not in universe) 100 No walls 200 Cardboard, scrap, and miscellaneous materials 201 Waste, scrap, or discarded material 202 Fabric or discarded material 203 Zinc, fabric, cardboard, tins, and waste material 204 Cardboard sheet 205 Plastic sheeting, cardboard 206 Makeshift, salvaged, or improvised materials 207 Reused materials 300 Wood 310 Rough wood 320 Wood, fibercement or plywood 330 Wood, formica, and other 340 Wood or bamboo 350 Wood or straw 400 Other plant-based materials 401 Plantain leaves and similar material 402 Bamboo or cane 403 Bamboo, sawali, cogon, nipa 404 Straw or bamboo 405 Grass, straw or reed 406 Reed, bamboo, or palm 407 Cane, palm leaves, logs 408 Palm leaves or palm planks 409 Bark, sticks, or cane 500 Masonry, stone, cement, adobe, metal, glass, and other fabricated materials (sometimes mixed with wood) 501 Brick, block, stone, or cement 502 Brick, stone, concrete 503 Brick, stone, or substitutes (dividing panels made of reinforced concrete) 504 Brick, stone, or substitutes (dividing panels made of wood) 505 Brick or tile 506 Brick or stone 507 Brick or cement block 508 Brick with plaster exterior 509 Brick without plaster exterior 510 Burnt or stabilized brick 511 Covered brick 512 Brick 513 Unburnt brick 514 Unburnt brick with cement 515 Unburnt brick with mud 516 Concrete 517 Landcrete, sandcrete 518 Cement blocks 519 Cement blocks or brick 520 Cement blocks or brick, unfinished 521 Cement and adobe bricks 522 Cement and stone block 523 Cement and tiles 524 Reinforced concrete, pre-cast concrete panels, or steel skeleton framed concrete 525 Concrete, reinforced concrete, blocks, panels 526 Fibercement 527 Adobe 528 Adobe walls with plaster exterior 529 Adobe walls without plaster exterior 530 Adobe with cement exterior 531 Wood and earth adobe 532 Wood and cement adobe 533 Mud or adobe 534 Pressed dirt 535 Clay 536 Coated clay/mud with sticks/cane 537 Clay or clay-covered sticks 538 Netted bamboo or cane with mud 539 Bundle of mud, straw, other materials 540 Mud with wood/wattle 541 Pole and mud 542 Mud with cement 543 Unfinished lathe and plaster, stucco, etc. 544 Stone 545 Hand-laid stone 546 Quarried stone 547 Cut stone and concrete 548 Cemented stone 549 Stone with clay 550 Blocks of light material 551 Prefabricated material 552 Asbestos 553 Metal or asbestos sheet 554 Metal or iron sheet 555 Metal or fibercement sheeting 556 Galvanized iron or aluminum 557 Tin 558 Glass 559 Cloth 560 Covintec panels 561 Mixed material 562 Mixed material: part wood; part concrete, brick, or stone 563 Wood plastered with clay, adobe, other materials; wood pressed panels; rolled mud bricks; etc. 564 Mixed material: wood or galvanized metal 570 Mainly permanent materials 600 Other material 601 Partition wall, lined with wood or steel 602 Partition wall, unlined 999 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Roof material This variable indicates the dwelling's predominant roofing material. 00 NIU (not in universe) 10 Masonry, concrete, clay tile, or tiles of unspecified type 11 Concrete or cement 12 Reinforced concrete (slab) 13 Cement or sheet metal 14 Tile, unspecified material 15 Clay tile 16 Tile or cement 17 Modern tiles, industrial 18 Traditional tiles, locally made 19 Tile or flat stone 20 Tile, unspecified or mixed materials 21 Fibercement or plastic 22 Fibercement or metal sheets 23 Asphalt or laminate cover 24 Tile, cement, asphalt 25 Asphalt tile 26 Slate or tile 27 Slate or asbestos 28 Asbestos 29 Adobe 30 Tiles or wood planks 31 Roofing shingles 32 Tar paper 33 Metal 34 Sheet metal 35 Zinc or tin 36 Tin 37 Sheet metal or other sheet material 38 Sheet metal, tile, slate 40 Wood and other plant materials 41 Wood 42 Wood, including bamboo 43 Bamboo 44 Cogon, nipa, anahaw 45 Thatch (straw, grass, leaves, palm, etc.) 46 Cane, wood, straw 47 Grass or straw 48 Papyrus 49 Banana leaves or fiber 50 Palm or makuti 51 Straw, bamboo, polythene 52 Wood with clay 53 Grass and mud 54 Rustic mat 60 Mud or earth 61 Clay 70 Cardboard, scrap, and miscellaneous materials 71 Discarded or scrap material 72 Cardboard 73 Plastic, tarpaulin 80 Other, unspecified 90 No roof 99 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Household classification HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable Constructed Household Variables -- HOUSEHOLD Number of families in household NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. 0 Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families Constructed Household Variables -- HOUSEHOLD Number of married couples in household NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). 0 No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples Constructed Household Variables -- HOUSEHOLD Number of mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). 0 No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household Constructed Household Variables -- HOUSEHOLD Number of fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). 0 No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household Constructed Household Variables -- HOUSEHOLD Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. Constructed Household Variables -- HOUSEHOLD Dwelling number Myanmar 2014: All records This variable indicates the dwelling number. This is a 10-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Myanmar 2014: All records This variable indicates the number of persons in the household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 Technical Household Variables -- HOUSEHOLD Dwelling created by splitting apart a large dwelling or household Myanmar 2014: All records This variable indicates if the dwelling was created by splitting apart a large dwelling or household. 0 No problem 1 Yes: households within a large dwelling were split apart into separate dwellings 2 Yes: persons within a large household were split apart into separate dwellings Technical Household Variables -- HOUSEHOLD Type of residence <span class="h2">Housing characteristics</span></p> <p><span class="h3">32. Type of housing unit occupied by this household</span><div class="i1">[] 1. Condominium<br />[] 2. Apartment / flat<br />[] 3. Bungalow / brick house<br />[] 4. Semi-pacca house [semi-permanent] <br />[] 5. Wooden house<br />[] 6. Bamboo<br />[] 7. Hut 2-3 years<br />[] 8. Hut 1 year<br />[] 9. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates the type of dwelling occupied by the household. 0 NIU (not in universe) 1 Condominium, apartment, flat 2 Bungalow, brick house 3 Semi-pacca house 4 Wooden house 5 Bamboo 6 Hut 2 - 3 years 7 Hut 1 year 8 Other Dwelling Characteristics Variables -- HOUSEHOLD Type of ownership <span class="h2">Housing characteristics</span></p> <p><span class="h3">33. Type of ownership of housing unit</span><div class="i1">[] 1. Owner<br />[] 2. Renter<br />[] 3. Provided free (individual)<br />[] 4. Government quarter<br />[] 5. Private company quarter<br />[] 6. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates the type of ownership of the dwelling. 0 NIU (not in universe) 1 Owner 2 Renter 3 Provided free (individual) 4 Government quarters 5 Private company quarters 6 Other Household Economic Variables -- HOUSEHOLD Lighting <span class="h2">Housing characteristics</span></p> <p><span class="h3">34. Main source of lighting in the household</span><div class="i1">[] 1. Electricity<br />[] 2. Kerosene<br />[] 3. Candle<br />[] 4. Battery<br />[] 5. Generator (private)<br />[] 6. Water mill (private)<br />[] 7. Solar system / energy<br />[] 8. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates what type of lighting is used by the household. 0 NIU (not in universe) 1 Electricity 2 Kerosene 3 Candle 4 Battery 5 Generator (private) 6 Water mill (private) 7 Solar system or solar energy 8 Other Utilities Variables -- HOUSEHOLD Drinking water <span class="h2">Housing characteristics</span></p> <p><span class="h3">35. Main source of water for drinking and non-drinking in this household</span></p> <p><span class="em">Drinking </span><div class="i1">[] 1. Tap water / piped<br />[] 2. Tube well, borehole<br />[] 3. Protected well / spring<br />[] 4. Unprotected well / spring<br />[] 5. Pool / pond / lake<br />[] 6. River / stream / canal<br />[] 7. Waterfall / rain water<br />[] 8. Bottled water / water from vending machine<br />[] 9. Tanker / truck<br />[] 10. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates what type of drinking water is used by the household. 00 NIU (not in universe) 01 Tap water, piped 02 Tube well, borehole 03 Protected well, spring 04 Unprotected well, spring 05 Pool, pond, or lake 06 River, stream, or canal 07 Waterfall, rain water 08 Bottled water, water from vending machine 09 Tanker, truck 10 Other Utilities Variables -- HOUSEHOLD Non-drinking water <span class="h2">Housing characteristics</span></p> <p><span class="h3">35. Main source of water for drinking and non-drinking in this household</span></p> <p><span class="em">Non-drinking</span><div class="i1">[] 1. Tap water / piped<br />[] 2. Tube well, borehole<br />[] 3. Protected well / spring<br />[] 4. Unprotected well / spring<br />[] 5. Pool / pond / lake<br />[] 6. River / stream / canal<br />[] 7. Waterfall / rain water<br />[] 8. Bottled water/water from vending machine<br />[] 9. Tanker / truck<br />[] 10. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates what type of non-drinking water is used by the household. 00 NIU (not in universe) 01 Tap water, piped 02 Tube well, borehole 03 Protected well, spring 04 Unprotected well, spring 05 Pool, pond, or lake 06 River, stream, or canal 07 Waterfall, rain water 08 Bottled water, water from vending machine 09 Tanker, truck 10 Other Utilities Variables -- HOUSEHOLD Cooking fuel <span class="h2">Housing characteristics</span></p> <p><span class="h3">36. Main type of cooking fuel used in this household</span><div class="i1">[] 1. Electricity<br />[] 2. Liquefied Petroleum Gas (LPG)<br />[] 3. Kerosene<br />[] 4. BioGas<br />[] 5. Firewood<br />[] 6. Charcoal<br />[] 7. Coal<br />[] 8. Straw / grass<br />[] 9. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates what type of cooking fuel is used by the household. 0 NIU (not in universe) 1 Electricity 2 Liquefied Petroleum Gas (LPG) 3 Kerosene 4 BioGas 5 Firewood 6 Charcoal 7 Coal 8 Straw, grass 9 Other Utilities Variables -- HOUSEHOLD Toilet <span class="h2">Housing characteristics</span></p> <p><span class="h3">37. Type of toilet used in this household</span><div class="i1">[] 1. Flush<br />[] 2. Water Seal (Improved PL)<br />[] 3. Pit (Traditional pit latrine)<br />[] 4. Bucket (Surface latrine)<br />[] 5. Other<br />[] 6. No toilet</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates what type of toilet is used by the household. 0 NIU (not in universe) 1 Flush 2 Water seal (improved pit latrine) 3 Pit (traditional pit latrine) 4 Bucket (surface latrine) 5 Other 6 No toilet Dwelling Characteristics Variables -- HOUSEHOLD Roof <span class="h2">Housing characteristics</span></p> <p><span class="h3">38. Main construction material of the housing unit</span></p> <p><span class="em">Roof</span><div class="i1">[] 1. <span class="lang">Dhani </span> [nipa palm] / <span class="lang">Theke</span> / in leaf<br />[] 2. Bamboo<br />[] 3. Earth<br />[] 4. Wood<br />[] 5. Corrugated sheet<br />[] 6. Tile / brick / concrete<br />[] 7. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates the materials of the roof of the dwelling. 0 NIU (not in universe) 1 Dhani, theke, leaf 2 Bamboo 3 Wood 4 Corrugated sheet 5 Tile, brick, concrete 6 Other Dwelling Characteristics Variables -- HOUSEHOLD Walls <span class="h2">Housing characteristics</span></p> <p><span class="h3">38. Main construction material of the housing unit</span></p> <p><span class="em">Wall</span><div class="i1">[] 1. <span class="lang">Dhani </span> [nipa palm] / <span class="lang">Theke</span> / in leaf<br />[] 2. Bamboo<br />[] 3. Earth<br />[] 4. Wood<br />[] 5. Corrugated sheet<br />[] 6. Tile / brick / concrete<br />[] 7. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates the materials of the walls of the dwelling. 0 NIU (not in universe) 1 Dhani, theke, leaf 2 Bamboo 3 Earth 4 Wood 5 Corrugated sheet 6 Tile, brick, concrete 7 Other Dwelling Characteristics Variables -- HOUSEHOLD Floor <span class="h2">Housing characteristics</span></p> <p><span class="h3">38. Main construction material of the housing unit</span></p> <p><span class="em">Floor</span><div class="i1">[] 1. <span class="lang">Dhani </span> [nipa palm] / <span class="lang">Theke</span> / in leaf<br />[] 2. Bamboo<br />[] 3. Earth<br />[] 4. Wood<br />[] 5. Corrugated sheet<br />[] 6. Tile / brick / concrete<br />[] 7. Other</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates the materials of the floor of the dwelling. 0 NIU (not in universe) 2 Bamboo 3 Earth 4 Wood 5 Tile, brick, concrete 6 Other Dwelling Characteristics Variables -- HOUSEHOLD Radio <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Radio</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a radio. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Television <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Television</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a television. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Landline phone <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Landline phone</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a landline phone. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Mobile phone <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Mobile phone</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a mobile phone. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Computer <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Computer</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a computer. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Internet at home <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Internet at home</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has Internet. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Car, truck, or van <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Car / pick-up / truck / van</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a car, truck, or van. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Motorcycle or moped <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Motorcycle / moped / <span class="lang">Tuk Tuk</span></span> [auto rickshaw]</p> <div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a motorcycle or moped. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Bicycle <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Bicycle</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a bicycle. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Four wheel tractor <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">4-wheel tractor</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a four wheel tractor. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Canoe boat <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Canoe / boat</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a canoe or a boat without a motor. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Motor boat <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Motor boat</span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a motor boat. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Bullock cart <span class="h2">Housing characteristics</span></p> <p><span class="h3">39. Which of the following items does your household have?(mark all that apply)</span></p> <p><span class="em">Cart (Bullock) [pulled by oxen or cattle] </span><div class="i1">[] 1. Yes<br />[] 2. No</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates if the household has a bullock cart. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household type 55. Conventional household: Refers to one or more persons who usually share their living quarters (single quarter or compound) and share their meals. In common usage, it might be said that a household consists of "all persons living and eating together or eating from the same cooking-pot". They may be residing in several structures within a compound like in the rural areas.</p> <p>59. Institution household: There are cases where certain rules used to decide what a conventional household is do not apply. Here are some guidelines to help you:</p> <p>60. Sometimes groups of people live together but cannot be said to belong to a conventional "ordinary" household. Examples are: old people's homes, orphanages, hospitals and rehabilitation centers, including children's hospitals and psychiatric hospitals, boarding schools, hotels, hostels and inns, institutions for people with disabilities, prisons and other penal institutions, religious centers - including monasteries and convents, camps for workers, military and police barracks, etc.</p> <p>61. In this census, the above groups of living arrangement is referred to as institution population. Note, within some institutions there will be both conventional households and institution households. For example, within a hospital there may be administrators living within the compound in a normal household set-up. Such will be referred to as conventional while the patients will be covered as institution households. Myanmar 2014: All households This variable indicates the form type. 1 Conventional household 2 Institution Group Quarters Variables -- HOUSEHOLD Household weight Myanmar 2014: All households This variable indicates the household weight. This is a 6-digit numeric variable with 4 implied decimal places Technical Household Variables -- HOUSEHOLD Urban or rural <span class="h2">Household identification</span><div class="i1">_ _ State Region<br />_ _ District<br />_ _ Township / sub township<br />_ _ _ Ward / village tract<br />_ Urban or rural<br />_ _ _ Enumeration area (Block no.)<br />_ _ _ Household no.</div> <span class="h3">Part 1: Household identification </span></p> <p>97. Each household and hence each questionnaire used must have a unique identification number:</p> <div class="i1">a. State/Region</div><div class="i2">Two digits</div><div class="i1">b. District</div><div class="i2">Two digits</div><div class="i1">c. Township</div><div class="i2">Two digits</div><div class="i1">d. Ward/Village Tract</div><div class="i2">Three digits</div><div class="i1">e. Rural/Urban</div><div class="i2">One digits</div><div class="i1">f. Enumeration area (Block No.)</div><div class="i2">Three digits</div><div class="i1">g. Household number</div><div class="i2">Three digits</div><div class="i1">In total 16 digits. Urban/rural is an important census division. If the EA is in a Ward mark option "1" (Urban) or if in a Village Tract then mark "2" (Rural).</div> Myanmar 2014: Conventional households [discrepancies: none] This variable indicates whether the household is located in an urban or rural area. 1 Urban 2 Rural 8 Unknown 9 NIU (not in universe) Geography: F-N Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother Constructed Family Interrelationship Variables -- PERSON Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father Constructed Family Interrelationship Variables -- PERSON Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse Constructed Family Interrelationship Variables -- PERSON Rule for linking parent PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap Constructed Family Interrelationship Variables -- PERSON Rule for linking spouse SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) Constructed Family Interrelationship Variables -- PERSON Probable stepmother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. In cases where a mother is linked to more children than she reports in CHBORN or CHSURV, the determination of which children to flag as probable stepchildren is based first on the strength of the child-mother pairing (see PARRULE), and then on the order of children in the household roster. Since most links to a given mother will be made at the same strength level, order will often be the decisive factor in flagging probable stepmother relationships. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. 0 Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother Constructed Family Interrelationship Variables -- PERSON Probable stepfather STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. 0 Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female Constructed Family Interrelationship Variables -- PERSON Man with more than one wife linked POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Woman is second or higher order wife POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. Constructed Family Interrelationship Variables -- PERSON Number of own family members in household FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons Constructed Family Interrelationship Variables -- PERSON Number of own children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household Constructed Family Interrelationship Variables -- PERSON Number of own children under age 5 in household NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age Constructed Family Interrelationship Variables -- PERSON Age of eldest own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Age of youngest own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Relationship to household head [general version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown Demographic Variables -- PERSON Relationship to household head [detailed version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown Demographic Variables -- PERSON Age AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing Demographic Variables -- PERSON Age, grouped into intervals AGE2 gives computed years of age grouped into intervals. 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown Demographic Variables -- PERSON Sex SEX reports the sex (gender) of the respondent. 1 Male 2 Female 9 Unknown Demographic Variables -- PERSON Marital status [general version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 0 NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing Demographic Variables -- PERSON Marital status [detailed version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 000 NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 219 Married, spouse absent (historical samples) 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing Demographic Variables -- PERSON Children ever born CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children surviving CHSURV reports the number of children born to a woman who were still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children ever born CHBORNF indicates the number of female children ever born to a woman. Only live births are counted. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children ever born CHBORNM indicates the number of male children ever born to a woman. Only live births are counted. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of last birth LASTBMO indicates the month of birth of the last child born by the respondent. The data refer to live births. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of last birth LASTBYR indicates the year of birth of the last child born by the respondent. The data refer to live births. 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Unknown 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Sex of last birth LASTBSEX indicates the sex of a woman's most recent birth. 0 NIU (not in universe) 1 Male 2 Female 3 Both sexes (multiple births) 9 Unknown Fertility and Mortality Variables -- PERSON Number of children dead CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown/missing 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children dead CHDEADFEM indicates the number of female children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Female children ever born" and "Female children surviving" variables. That is not done in CHDEADFEM, which includes only the samples that directly reported the information in the appropriate form. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children dead CHDEADMALE indicates the number of male children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Male children ever born" and "Male children surviving" variables. That is not done in CHDEADMALE, which includes only the samples that directly reported the information in the appropriate form. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of last birth LASTBMORT indicates the mortality status of the last child born to a woman. There is no constraint on how long ago the child may have been born. Only live births are considered. 0 NIU (not in universe) 1 Alive 2 Dead 9 Unknown Fertility and Mortality Variables -- PERSON Number of own children in household HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own female children in household HOMEFEM indicates the number of female children born living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 17 17 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own male children in household HOMEMALE indicates the number of male children born living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own children living elsewhere AWAYCHILD indicates the number of surviving biological children not living in the household with their mother (the respondent) at the time of the census. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own female children living elsewhere AWAYFEM indicates the number of surviving biological female children not living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own male children living elsewhere AWAYMALE indicates the number of surviving biological male children not living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Country of birth BPLCOUNTRY indicates the person's country of birth. 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11005 British Indian Ocean Territory 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11051 Ethiopia (including Eritrea) 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15021 Upper Volta 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15081 Guinea-Bissau and Cape Verde 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15180 Canary Islands 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Croix 21210 St. John 21220 St. Lucia 21230 St Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21991 Caribbean commonwealth, n.s. 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32042 India/Pakistan/Bangladesh/Sri Lanka 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32101 Pakistan/Bangladesh 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34071 Israel/Palestine 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34111 West Bank 34112 Gaza Strip 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41991 Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43121 Spain/Portugal 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43991 Gibraltar/Malta 43992 Portugal/Greece 43993 Italy, Holy See, San Marino 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44042 West Germany 44043 Germany/Austria 44044 Mecklenburg-Schwerin 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44991 Belgium, Denmark, Luxembourg, Netherlands 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53060 Federated States of Micronesia 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 80000 AT SEA 90000 Other countries n.s. 99999 Unknown Nativity and Birthplace Variables -- PERSON Region or state of birth, Myanmar BPLMM1 indicates the person's state of birth within Myanmar. 01 Kachin 02 Kayah 03 Kayin 04 Chin 05 Sagaing 06 Tanintharyi 07 Bago 08 Magway 09 Mandalay 10 Mon 11 Rakhine 12 Yangon 13 Shan 14 Ayeyawady 15 Nay Pyi Taw 97 Abroad 99 NIU Nativity and Birthplace Variables -- PERSON District of birth, Myanmar BPLMM2 indicates the person's district of birth within Myanmar. 0101 Myitkyina 0102 Mohnyin 0103 Bhamo 0104 Putao 0201 Loikaw 0202 Bawlakhe 0301 Hpa-An 0302 Pharpon 0303 Myawady 0304 Kawkareik 0401 Haka 0402 Falam 0403 Mindat 0501 Sagaing 0502 Shwebo 0503 Monywa 0504 Katha 0505 Kalay 0506 Tamu 0507 Mawlaik 0508 Hkamti 0509 Yinmarpin 0601 Dawei 0602 Myeik 0603 Kawthoung 0701 Bago 0702 Toungoo 0703 Pyay 0704 Thayawady 0801 Magway 0802 Minbu 0803 Thayet 0804 Pakokku 0805 Gangaw 0901 Mandalay 0902 Pyin Oo Lwin 0903 Kyaukse 0904 Myingyan 0905 Nyaung U 0906 Yame'Thin 0907 Meiktila 1001 Mawlamyine 1002 Thaton 1101 Sittway 1102 Myauk U 1103 Maungtaw 1104 Kyaukpyu 1105 Thandwe 1201 North Yangon 1202 East Yangon 1203 South Yangon 1204 West Yangon 1301 Taunggyi 1302 Loilin 1303 Linkhe' 1304 Lashio 1305 Muse 1306 Kyaukme 1307 Kunlon 1308 Laukine 1309 Hopan 1310 Makman 1311 Kengtung 1312 Minesat 1313 Tachileik 1314 Minephyat 1399 Shan region, district unknown 1401 Pathein 1402 Phyapon 1403 Maubin 1404 Myaungmya 1405 Labutta 1406 Hinthada 1501 Ottara (North) 1502 Dekkhina (South) 9997 Abroad 9999 NIU Nativity and Birthplace Variables -- PERSON School attendance SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. 0 NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing Education Variables -- PERSON Literacy LIT indicates whether or not the respondent could read and write in any language. A person is typically considered literate if he or she can both read and write. All other persons are illiterate, including those who can either read or write but cannot do both. 0 NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing Education Variables -- PERSON Educational attainment, international recode [general version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 0 NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown Education Variables -- PERSON Educational attainment, international recode [detailed version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing Education Variables -- PERSON Years of schooling YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2. Users should pay close attention to the top-codes in each sample, as discussed in the comparability section. 00 None or pre-school 01 1 year 02 2 years 03 3 years 04 4 years 05 5 years 06 6 years 07 7 years 08 8 years 09 9 years 10 10 years 11 11 years 12 12 years 13 13 years 14 14 years 15 15 years 16 16 years 17 17 years 18 18 years or more 90 Not specified 91 Some primary 92 Some technical after primary 93 Some secondary 94 Some tertiary 95 Adult literacy 96 Special education 98 Unknown/missing 99 NIU (not in universe) Education Variables -- PERSON Educational attainment, Myanmar EDUCMM indicates the person's educational attainment in Myanmar in terms of the level of schooling completed and the grades within that level. 00 NIU (not in universe) 10 No schooling 21 Primary, grade 1 22 Primary, grade 2 23 Primary, grade 3 24 Primary, grade 4 25 Primary, grade 5 31 Middle, grade 6 32 Middle, grade 7 33 Middle, grade 8 34 Middle, grade 9 41 High, grade 10 42 High, grade 11 51 College, attending 52 Vocational training, completed 53 Undergraduate diploma 54 Bachelor degree, graduate 55 Postgraduate diploma 56 Master degree 57 Doctoral degree 60 Other Education Variables -- PERSON Activity status (employment status) [general version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 0 NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing Work Variables -- PERSON Activity status (employment status) [detailed version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 301 Unavailable jobseekers 302 Available potential jobseekers 310 Housework 320 Health reasons, unable to work, or disabled 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing Work Variables -- PERSON Labor force participation LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Sector of employment EMPSECT indicates the economic sector in which the person was employed. Economic sector is defined in terms of ownership or control of the enterprise in which the person worked. 00 NIU (not in universe) 10 Public 20 Private 21 Private, not elsewhere classified 22 Individual/family enterprise, and self-employed 23 Foreign 30 Mixed: public-private or parastatal 40 Collective or cooperative 50 Foreign government or non-governmental organization 60 Other, unspecified 61 Canal zone 62 Faith-based organization 63 Informal sector 99 Unknown Work Variables -- PERSON Migration status, previous residence MIGRATEP indicates whether the person's most recent move (if any) was between minor administrative units, major units, or countries. 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 98 Response suppressed 99 Not reported/missing/unknown Migration: Global Variables -- PERSON 1st subnational geographic level of previous residence, world [consistent boundaries over time] GEOMIG1_P indicates the major administrative unit in which the person previously resided prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of previous residence, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_1 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_1, GEOMIG1_5, and GEOMIG1_10. More on migration and geography can be found here. 051901 Yerevan [Province: Armenia] 051902 Aragatsotn [Province: Armenia] 051903 Ararat [Province: Armenia] 051904 Armavir [Province: Armenia] 051905 Gegharkunik [Province: Armenia] 051906 Lori [Province: Armenia] 051907 Kotayk [Province: Armenia] 051908 Shirak [Province: Armenia] 051909 Syunik [Province: Armenia] 051910 Vayots Dzor [Province: Armenia] 051911 Tavush [Province: Armenia] 051912 Nagorno-Karabagh [Province: Armenia] 051997 Foreign country [Province: Armenia] 051998 Unknown [Province: Armenia] 051999 NIU (not in universe) [Province: Armenia] 112001 Brest [Region: Belarus] 112002 Vitebsk [Region: Belarus] 112003 Gomel [Region: Belarus] 112004 Grodno [Region: Belarus] 112006 Minsk, Minsk City [Region: Belarus] 112007 Mogilev [Region: Belarus] 112097 Foreign country [Region: Belarus] 112098 Unknown [Region: Belarus] 112099 NIU (not in universe) [Region: Belarus] 204001 Alibori [Department: Benin] 204002 Atacora [Department: Benin] 204003 Atlantique [Department: Benin] 204004 Borgou [Department: Benin] 204005 Collines [Department: Benin] 204006 Couffo [Department: Benin] 204007 Donga [Department: Benin] 204008 Littoral [Department: Benin] 204009 Mono [Department: Benin] 204010 Oueme [Department: Benin] 204011 Plateau [Department: Benin] 204012 Zou [Department: Benin] 204097 Abroad [Department: Benin] 204098 Unknown [Department: Benin] 204099 NIU (not in universe) [Department: Benin] 076011 Rondônia [State: Brazil] 076012 Acre [State: Brazil] 076013 Amazonas [State: Brazil] 076014 Roraima [State: Brazil] 076015 Pará [State: Brazil] 076016 Amapá [State: Brazil] 076021 Maranhão [State: Brazil] 076022 Piauí [State: Brazil] 076023 Ceará [State: Brazil] 076024 Rio Grande do Norte [State: Brazil] 076025 Paraíba [State: Brazil] 076026 Pernambuco, Arquipelago de Fernando de Noronha [State: Brazil] 076027 Alagoas [State: Brazil] 076028 Sergipe [State: Brazil] 076029 Bahia [State: Brazil] 076031 Minas Gerais [State: Brazil] 076032 Espírito Santo [State: Brazil] 076033 Rio de Janeiro, Guanabara [State: Brazil] 076035 São Paulo [State: Brazil] 076036 Serra dos Aimorés [State: Brazil] 076041 Paraná [State: Brazil] 076042 Santa Catarina [State: Brazil] 076043 Rio Grande do Sul [State: Brazil] 076051 Mato Grosso do Sul, Mato Grosso [State: Brazil] 076052 Goiás, Tocantins [State: Brazil] 076053 Distrito Federal [State: Brazil] 076054 Brazil, unspecified [State: Brazil] 076097 Abroad [State: Brazil] 076098 Unknown [State: Brazil] 076099 NIU (not in universe) [State: Brazil] 116001 Banteay Meanchey [Province: Cambodia] 116002 Battambang [Province: Cambodia] 116003 Kampong Cham, Tbong Khmum [Province: Cambodia] 116004 Kampong Chhnang [Province: Cambodia] 116005 Kampong Speu [Province: Cambodia] 116006 Kampong Thom [Province: Cambodia] 116007 Kampot [Province: Cambodia] 116008 Phnom Penh, Kandal [Province: Cambodia] 116009 Koh Kong, Preah Sihanouk [Province: Cambodia] 116010 Kratie [Province: Cambodia] 116011 Mondul Kiri [Province: Cambodia] 116013 Preah Vihear [Province: Cambodia] 116014 Prey Veng [Province: Cambodia] 116015 Pursat [Province: Cambodia] 116016 Ratanak Kiri [Province: Cambodia] 116017 Siem Reap, Otdar Meanchey [Province: Cambodia] 116019 Stung Treng [Province: Cambodia] 116020 Svay Rieng [Province: Cambodia] 116021 Takeo [Province: Cambodia] 116023 Kep [Province: Cambodia] 116024 Pailin [Province: Cambodia] 116097 Foreign country [Province: Cambodia] 116098 Unknown [Province: Cambodia] 116099 NIU (not in universe) [Province: Cambodia] 120002 Centre, Sud [Province: Cameroon] 120003 Est [Province: Cameroon] 120004 Nord, Adamoua, Extrème Nord [Province: Cameroon] 120005 Littoral [Province: Cameroon] 120007 Nord Ouest [Province: Cameroon] 120008 Ouest [Province: Cameroon] 120010 Sud Ouest [Province: Cameroon] 120096 Cameroon - unknown arrondissement [Province: Cameroon] 120097 Foreign country [Province: Cameroon] 120098 Unknown [Province: Cameroon] 120099 NIU (not in universe) [Province: Cameroon] 152001 Tarapaca [Province: Chile] 152002 Antofagasta [Province: Chile] 152003 Atacama [Province: Chile] 152004 Coquimbo [Province: Chile] 152005 Aconcagua [Province: Chile] 152006 Valparaíso [Province: Chile] 152007 Santiago [Province: Chile] 152008 O'Higgins [Province: Chile] 152009 Colchagua [Province: Chile] 152010 Curicó [Province: Chile] 152011 Talca [Province: Chile] 152012 Maule [Province: Chile] 152013 Linares [Province: Chile] 152014 Ñuble [Province: Chile] 152015 Concepción [Province: Chile] 152016 Arauco [Province: Chile] 152017 Bío Bío [Province: Chile] 152018 Malleco [Province: Chile] 152019 Cautín [Province: Chile] 152020 Valdivia [Province: Chile] 152021 Osorno [Province: Chile] 152022 Llanquihue [Province: Chile] 152023 Chiloé [Province: Chile] 152024 Aysén [Province: Chile] 152025 Magallanes [Province: Chile] 152097 Foreign country [Province: Chile] 152098 Unknown [Province: Chile] 152099 NIU (not in universe) [Province: Chile] 170005 Antioquia [Department: Colombia] 170008 Atlántico [Department: Colombia] 170011 Bogotá D.C., Cundinamarca [Department: Colombia] 170013 Bolívar, Sucre [Department: Colombia] 170015 Boyacá, Casanare [Department: Colombia] 170018 Caquetá [Department: Colombia] 170019 Cauca [Department: Colombia] 170023 Córdoba [Department: Colombia] 170027 Chocó [Department: Colombia] 170041 Huila [Department: Colombia] 170044 La Guajira [Department: Colombia] 170050 Meta [Department: Colombia] 170052 Nariño [Department: Colombia] 170054 Cesar, Norte De Santander, Magdalena [Department: Colombia] 170066 Caldas, Quindío, Risaralda [Department: Colombia] 170068 Santander [Department: Colombia] 170073 Tolima [Department: Colombia] 170076 Valle Del Cauca [Department: Colombia] 170081 Arauca [Department: Colombia] 170086 Putumayo [Department: Colombia] 170088 Archipiélago De San Andrés Y Providencia [Department: Colombia] 170095 Amazonas, Guaviare, Vaupés, Vichada, Guainía [Department: Colombia] 170097 Abroad [Department: Colombia] 170098 Unknown [Department: Colombia] 188001 San José [Province: Costa Rica] 188002 Alajuela [Province: Costa Rica] 188003 Cartago [Province: Costa Rica] 188004 Heredia [Province: Costa Rica] 188005 Guanacaste [Province: Costa Rica] 188006 Puntarenas [Province: Costa Rica] 188007 Limón [Province: Costa Rica] 188097 Foreign country [Province: Costa Rica] 188098 Unknown [Province: Costa Rica] 192021 Pinar del Río, Artemisa, Mayabeque [Province: Cuba] 192023 La Habana [Province: Cuba] 192025 Matanzas [Province: Cuba] 192026 Villa Clara [Province: Cuba] 192027 Cienfuegos [Province: Cuba] 192028 Sancti Spíritus [Province: Cuba] 192029 Ciego de Ávila [Province: Cuba] 192030 Camagüey [Province: Cuba] 192031 Las Tunas [Province: Cuba] 192032 Holguín [Province: Cuba] 192033 Granma [Province: Cuba] 192034 Santiago de Cuba [Province: Cuba] 192035 Guantánamo [Province: Cuba] 192040 Isla de la Juventud [Province: Cuba] 192997 Abroad [Province: Cuba] 192998 Unknown [Province: Cuba] 192999 NIU (not in universe) [Province: Cuba] 218001 Azuay [Province: Ecuador] 218002 Bolívar [Province: Ecuador] 218004 Carchi [Province: Ecuador] 218005 Cotopaxi [Province: Ecuador] 218006 Chimborazo [Province: Ecuador] 218007 El Oro [Province: Ecuador] 218009 Cañar, Esmeraldas, Guayas, Manabí, Manga del Cura [Disputed canton], Pichincha, El Piedrero [Disputed canton], Los Ríos, Santa Elena, Santo Domingo de las Tsáchilas, Galápagos [Province: Ecuador] 218010 Imbabura, Las Golondrinas [Disputed canton] [Province: Ecuador] 218011 Loja [Province: Ecuador] 218014 Morona Santiago [Province: Ecuador] 218016 Pastaza [Province: Ecuador] 218018 Tungurahua [Province: Ecuador] 218019 Zamora Chinchipe [Province: Ecuador] 218021 Napo, Orellana, Sucumbíos [Province: Ecuador] 218097 Foreign country [Province: Ecuador] 218098 Unknown and Disputed Zones [Province: Ecuador] 218999 NIU (not in universe) [Province: Ecuador] 818000 Reported same governorate as household location [Governorate: Egypt] 818001 Giza, 6th October City, Cairo, Helwan [Governorate: Egypt] 818002 Alexandria [Governorate: Egypt] 818003 Port Said [Governorate: Egypt] 818004 Suez [Governorate: Egypt] 818011 Demietta [Governorate: Egypt] 818012 Dakahlia [Governorate: Egypt] 818013 Sharkia [Governorate: Egypt] 818014 Kaliobia [Governorate: Egypt] 818015 Kafr Sheikh [Governorate: Egypt] 818016 Gharbia [Governorate: Egypt] 818018 Menoufia, Behera [Governorate: Egypt] 818019 Ismailia [Governorate: Egypt] 818022 Bani Swif [Governorate: Egypt] 818023 Fayoum [Governorate: Egypt] 818024 Menia [Governorate: Egypt] 818025 Asiut [Governorate: Egypt] 818026 Sohag [Governorate: Egypt] 818027 Qena, Luxor [Governorate: Egypt] 818028 Aswan [Governorate: Egypt] 818031 Red Sea [Governorate: Egypt] 818032 New Valley [Governorate: Egypt] 818033 Marsa Matroh [Governorate: Egypt] 818034 North Sinai [Governorate: Egypt] 818035 South Sinai [Governorate: Egypt] 818097 Abroad [Governorate: Egypt] 818098 Unknown [Governorate: Egypt] 818099 NIU (not in universe) [Governorate: Egypt] 222001 Ahuachapán [Department: El Salvador] 222002 Santa Ana [Department: El Salvador] 222003 Sonsonate [Department: El Salvador] 222004 Chalatenango [Department: El Salvador] 222005 La Libertad [Department: El Salvador] 222006 San Salvador [Department: El Salvador] 222007 Cuscatlán [Department: El Salvador] 222008 La Paz [Department: El Salvador] 222009 Cabañas [Department: El Salvador] 222010 San Vicente [Department: El Salvador] 222011 Usulután [Department: El Salvador] 222012 San Miguel [Department: El Salvador] 222013 Morazán [Department: El Salvador] 222014 La Unión [Department: El Salvador] 222098 Abroad [Department: El Salvador] 222099 NIU (not in universe) [Department: El Salvador] 231001 Tigray [Region: Ethiopia] 231002 Affar [Region: Ethiopia] 231003 Amhara [Region: Ethiopia] 231004 Oromia, Somali [Region: Ethiopia] 231006 Benishangul-Gumuz [Region: Ethiopia] 231007 Southern Nations, Nationalities, and Peoples (SNNP) [Region: Ethiopia] 231012 Gambela [Region: Ethiopia] 231013 Harari [Region: Ethiopia] 231014 Addis Ababa [Region: Ethiopia] 231015 Dire Dawa [Region: Ethiopia] 231097 Abroad [Region: Ethiopia] 231099 NIU [Region: Ethiopia] 250001 Guadeloupe [Region: France] 250002 Martinique [Region: France] 250003 French Guyana [Region: France] 250004 Réunion Island [Region: France] 250011 Île-de-France [Region: France] 250021 Champagne-Ardenne [Region: France] 250022 Picardy [Region: France] 250023 Upper Normandy [Region: France] 250024 Centre [Region: France] 250025 Lower Normandy [Region: France] 250026 Burgundy [Region: France] 250031 North Pas-de-Calais [Region: France] 250041 Lorraine [Region: France] 250042 Alsace [Region: France] 250043 Franche-Comté [Region: France] 250052 Loire Valley [Region: France] 250053 Brittany [Region: France] 250054 Poitou-Charentes [Region: France] 250072 Aquitaine [Region: France] 250073 Midi-Pyrénées [Region: France] 250074 Limousin [Region: France] 250082 Rhône-Alpes [Region: France] 250083 Auvergne [Region: France] 250091 Languedoc-Roussillon [Region: France] 250093 Provence-Alpes-Riviera [Region: France] 250094 Corsica [Region: France] 250097 Abroad [Region: France] 320001 Guatemala [Department: Guatemala] 320002 El Progreso [Department: Guatemala] 320003 Sacatepéquez [Department: Guatemala] 320004 Chimaltenango [Department: Guatemala] 320005 Escuintla [Department: Guatemala] 320006 Santa Rosa [Department: Guatemala] 320007 Sololá [Department: Guatemala] 320008 Totonicapán [Department: Guatemala] 320009 Quetzaltenango [Department: Guatemala] 320010 Suchitepéquez [Department: Guatemala] 320011 Retalhuleu [Department: Guatemala] 320012 San Marcos [Department: Guatemala] 320013 Huehuetenango [Department: Guatemala] 320014 Quiché [Department: Guatemala] 320015 Baja Verapaz [Department: Guatemala] 320016 Alta Verapaz [Department: Guatemala] 320017 Petén [Department: Guatemala] 320018 Izabal [Department: Guatemala] 320019 Zacapa [Department: Guatemala] 320020 Chiquimula [Department: Guatemala] 320021 Jalapa [Department: Guatemala] 320022 Jutiapa [Department: Guatemala] 320097 Foreign Country [Department: Guatemala] 320098 Unknown [Department: Guatemala] 320099 NIU [Department: Guatemala] 324011 Boffa [Region: Guinea] 324012 Boké [Region: Guinea] 324013 Fria [Region: Guinea] 324014 Gaoual [Region: Guinea] 324015 Koundara [Region: Guinea] 324021 Conakry [Region: Guinea] 324031 Dabola [Region: Guinea] 324032 Dinguiraye [Region: Guinea] 324033 Faranah [Region: Guinea] 324034 Kissidougou [Region: Guinea] 324041 Kankan [Region: Guinea] 324042 Kérouané [Region: Guinea] 324043 Kouroussa [Region: Guinea] 324044 Mandiana [Region: Guinea] 324045 Siguiri [Region: Guinea] 324051 Coyah, Dubréka [Region: Guinea] 324053 Forécariah [Region: Guinea] 324054 Kindia [Region: Guinea] 324055 Télimélé [Region: Guinea] 324061 Koubia [Region: Guinea] 324062 Labé [Region: Guinea] 324063 Lélouma [Region: Guinea] 324064 Mali [Region: Guinea] 324065 Tougué [Region: Guinea] 324071 Dalaba [Region: Guinea] 324072 Mamou [Region: Guinea] 324073 Pita [Region: Guinea] 324081 Beyla [Region: Guinea] 324082 Guéckédou [Region: Guinea] 324083 Lola [Region: Guinea] 324084 Macenta [Region: Guinea] 324085 Nzerekore [Region: Guinea] 324086 Yomou [Region: Guinea] 324096 Guinea, place unknown [Region: Guinea] 324097 Foreign country [Region: Guinea] 324098 Unknown [Region: Guinea] 324099 NIU (not in universe) [Region: Guinea] 332003 Nord (North) and Nord'est (North East) [Department: Haiti] 332006 Centre (Central), L'Artibonite, Ouest (West), Sud'Est (South East) [Department: Haiti] 332007 Grand'Anse, Nippes, Sud (South) [Department: Haiti] 332009 Nord'Ouest (North West) [Department: Haiti] 332097 Foreign Country [Department: Haiti] 332098 Unknown [Department: Haiti] 356001 Jammu and Kashmir [State: India] 356002 Himachal Pradesh [State: India] 356003 Punjab [State: India] 356004 Chandigarh [State: India] 356006 Haryana [State: India] 356007 Delhi [State: India] 356008 Rajasthan [State: India] 356009 Uttar Pradesh, Uttaranchal [State: India] 356010 Bihar, Jharkhand [State: India] 356011 Sikkim [State: India] 356012 Arunachal Pradesh [State: India] 356013 Nagaland [State: India] 356014 Manipur [State: India] 356015 Mizoram [State: India] 356016 Tripura [State: India] 356017 Meghalaya [State: India] 356018 Assam [State: India] 356019 West Bengal [State: India] 356021 Orissa [State: India] 356023 Madhya Pradesh, Chhattisgarh [State: India] 356024 Gujarat [State: India] 356026 Dadra and Nagar Haveli [State: India] 356027 Maharashtra [State: India] 356028 Andhra Pradesh [State: India] 356029 Karnataka [State: India] 356030 Goa, Daman and Diu [State: India] 356031 Lakshadweep [State: India] 356032 Kerala [State: India] 356033 Tamil Nadu [State: India] 356034 Pondicherry [State: India] 356035 Andaman and Nicobar Islands [State: India] 356097 Abroad [State: India] 356098 Unknown [State: India] 356099 NIU (not in universe) [State: India] 360011 Nanggroe Aceh Darussalam [Province: Indonesia] 360012 Sumatera Utara [Province: Indonesia] 360013 Sumatera Barat [Province: Indonesia] 360014 Kepulauan Riau, Riau [Province: Indonesia] 360015 Jambi [Province: Indonesia] 360016 Bangka Belitung, Sumatera Selatan [Province: Indonesia] 360017 Bengkulu [Province: Indonesia] 360018 Lampung [Province: Indonesia] 360031 DKI Jakarta [Province: Indonesia] 360032 Banten, Jawa Barat [Province: Indonesia] 360033 Jawa Tengah [Province: Indonesia] 360034 DKI Yogyakarta [Province: Indonesia] 360035 Jawa Timur [Province: Indonesia] 360051 Bali [Province: Indonesia] 360052 Nusa Tenggara Barat [Province: Indonesia] 360053 Nusa Tenggara Timur [Province: Indonesia] 360061 Kalimantan Barat [Province: Indonesia] 360062 Kalimantan Tengah [Province: Indonesia] 360063 Kalimantan Selatan [Province: Indonesia] 360064 Kalimantan Timur [Province: Indonesia] 360071 Gorontalo, Sulawesi Utara [Province: Indonesia] 360072 Sulawesi Tengah [Province: Indonesia] 360073 Sulawesi Barat, Sulawesi Selatan [Province: Indonesia] 360074 Sulawesi Tenggara [Province: Indonesia] 360081 Maluku, Maluku Utara [Province: Indonesia] 360094 Papua, Papua Barat [Province: Indonesia] 360097 Abroad [Province: Indonesia] 360098 Unknown [Province: Indonesia] 360099 NIU (not in universe) [Province: Indonesia] 360626 East Timor [Province: Indonesia] 364000 Markazi [Province: Iran] 364001 Gilan [Province: Iran] 364002 Mazandaran [Province: Iran] 364003 East Azarbayejan [Province: Iran] 364004 West Azarbayejan [Province: Iran] 364005 Kermanshah [Province: Iran] 364006 Khuzestan [Province: Iran] 364007 Fars [Province: Iran] 364008 Kerman [Province: Iran] 364009 Razavi Khorasan [Province: Iran] 364010 Esfahan [Province: Iran] 364011 Sistan and Baluchestan [Province: Iran] 364012 Kordestan [Province: Iran] 364013 Hamedan [Province: Iran] 364014 Chaharmahal and Bakhtiyari [Province: Iran] 364015 Lorestan [Province: Iran] 364016 Ilam [Province: Iran] 364017 Kohgiluyeh and Boyerahmad [Province: Iran] 364018 Bushehr [Province: Iran] 364019 Zanjan [Province: Iran] 364020 Semnan [Province: Iran] 364021 Yazd [Province: Iran] 364022 Hormozgan [Province: Iran] 364023 Tehran, Alborz [Province: Iran] 364024 Ardebil [Province: Iran] 364025 Qom [Province: Iran] 364026 Qazvin [Province: Iran] 364027 Golestan [Province: Iran] 364028 North Khorasan [Province: Iran] 364029 South Khorasan [Province: Iran] 364098 Unknown [Province: Iran] 364099 NIU (not in universe) [Province: Iran] 368000 Always lived in residential place of birth [Governorate: Iraq] 368001 In this governorate [Governorate: Iraq] 368011 Dahuk [Governorate: Iraq] 368012 Nineveh [Governorate: Iraq] 368013 Sulaymaniyah [Governorate: Iraq] 368014 Al-Tameem [Governorate: Iraq] 368015 Erbil [Governorate: Iraq] 368021 Diala [Governorate: Iraq] 368022 Al-Anbar [Governorate: Iraq] 368023 Baghdad [Governorate: Iraq] 368024 Babylon [Governorate: Iraq] 368025 Kerbela [Governorate: Iraq] 368026 Wasit [Governorate: Iraq] 368027 Salah Al-Deen [Governorate: Iraq] 368028 Al-Najaf [Governorate: Iraq] 368031 Al-Qadisiya [Governorate: Iraq] 368032 Al-Muthanna [Governorate: Iraq] 368033 Thi-Qar [Governorate: Iraq] 368034 Maysan [Governorate: Iraq] 368035 Al-Basrah [Governorate: Iraq] 368097 Other countries [Governorate: Iraq] 368098 Unknown [Governorate: Iraq] 388001 Kingston [Parish: Jamaica] 388002 Saint Andrew [Parish: Jamaica] 388003 Saint Thomas [Parish: Jamaica] 388004 Portland [Parish: Jamaica] 388005 Saint Mary [Parish: Jamaica] 388006 Saint Ann [Parish: Jamaica] 388007 Trelawny [Parish: Jamaica] 388008 Saint James [Parish: Jamaica] 388009 Hanover [Parish: Jamaica] 388010 Westmoreland [Parish: Jamaica] 388011 Saint Elizabeth [Parish: Jamaica] 388012 Manchester [Parish: Jamaica] 388013 Clarendon [Parish: Jamaica] 388014 Saint Catherine [Parish: Jamaica] 388098 Unknown [Parish: Jamaica] 388099 NIU (Not in universe) [Parish: Jamaica] 400011 Amman [Governorate: Jordan] 400012 Balqa [Governorate: Jordan] 400013 Zarqa [Governorate: Jordan] 400014 Madaba [Governorate: Jordan] 400021 Irbid [Governorate: Jordan] 400022 Mafraq [Governorate: Jordan] 400023 Jarash [Governorate: Jordan] 400024 Ajlun [Governorate: Jordan] 400031 Karak [Governorate: Jordan] 400032 Tafilah [Governorate: Jordan] 400033 Ma'an [Governorate: Jordan] 400034 Aqaba [Governorate: Jordan] 400997 Foreign Country [Governorate: Jordan] 400998 Unknown [Governorate: Jordan] 404001 Nairobi [Province: Kenya] 404002 Central [Province: Kenya] 404003 Coast [Province: Kenya] 404004 Eastern [Province: Kenya] 404005 Northeastern [Province: Kenya] 404006 Nyanza [Province: Kenya] 404007 Rift Valley [Province: Kenya] 404008 Western [Province: Kenya] 404097 Abroad [Province: Kenya] 404098 Unknown [Province: Kenya] 404099 NIU (not in universe) [Province: Kenya] 417001 Bishkek [Region: Kyrgyz Republic] 417002 Issyk-Kul region [Region: Kyrgyz Republic] 417003 Dzhalal-Abad region [Region: Kyrgyz Republic] 417004 Naryn region [Region: Kyrgyz Republic] 417005 Batken region [Region: Kyrgyz Republic] 417006 Oshskaya region, City of Osh [Region: Kyrgyz Republic] 417007 Talasskaya region [Region: Kyrgyz Republic] 417008 Chuya region [Region: Kyrgyz Republic] 417096 Other Kyrgyz Republic, not specified [Region: Kyrgyz Republic] 417097 Foreign country [Region: Kyrgyz Republic] 417098 Unknown [Region: Kyrgyz Republic] 417099 NIU (not in universe) [Region: Kyrgyz Republic] 418001 Vientiane Capital [Province: Laos] 418002 Phongsaly [Province: Laos] 418003 Luangnamtha [Province: Laos] 418004 Oudomxay [Province: Laos] 418005 Bokeo [Province: Laos] 418006 Luangprabang [Province: Laos] 418007 Huaphanh [Province: Laos] 418008 Xayaboury [Province: Laos] 418009 Xienkhuang [Province: Laos] 418010 Vientiane Province [Province: Laos] 418011 Borikhamxay [Province: Laos] 418012 Khammuane [Province: Laos] 418013 Savanakhet [Province: Laos] 418014 Saravane [Province: Laos] 418015 Sekong [Province: Laos] 418016 Champasack [Province: Laos] 418017 Attapeu [Province: Laos] 418018 Xaysomboune [Province: Laos] 418097 Foreign Country [Province: Laos] 418098 Unknown [Province: Laos] 418099 NIU [Province: Laos] 662003 Castries city, Castries rural, Castries suburban [District: Saint Lucia] 662009 Choiseul, Laborie, Vieux-Fort [District: Saint Lucia] 662010 Anse-la-Raye, Canaries, Micoud, Soufriere [District: Saint Lucia] 662012 Dennery, Gros-Islet [District: Saint Lucia] 662098 Unknown [District: Saint Lucia] 662099 NIU [District: Saint Lucia] 454101 Chitipa [District: Malawi] 454102 Karonga [District: Malawi] 454103 Nkhata Bay, Likoma [District: Malawi] 454104 Rumphi [District: Malawi] 454105 Mzimba, Mzuzu City [District: Malawi] 454201 Kasungu [District: Malawi] 454202 Nkhotakota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe, Lilongwe City [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba, Zomba City [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre, Blantyre City [District: Malawi] 454306 Mwanza, Neno [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454309 Phalombe [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454312 Balaka [District: Malawi] 454997 Abroad [District: Malawi] 454999 NIU (not in universe) [District: Malawi] 466001 Kayes [Region: Mali] 466002 Koulikoro [Region: Mali] 466003 Sikasso [Region: Mali] 466004 Ségou [Region: Mali] 466005 Mopti [Region: Mali] 466006 Tombouctou [Region: Mali] 466007 Gao, Kidal [Region: Mali] 466009 Bamako [Region: Mali] 466096 Mali, province unspecified [Region: Mali] 466097 Foreign country [Region: Mali] 466098 Unknown [Region: Mali] 466999 NIU (not in universe) [Region: Mali] 484001 Aguascalientes [State: Mexico] 484002 Baja California [State: Mexico] 484003 Baja California Sur [State: Mexico] 484004 Campeche [State: Mexico] 484005 Coahuila de Zaragoza [State: Mexico] 484006 Colima [State: Mexico] 484007 Chiapas [State: Mexico] 484008 Chihuahua [State: Mexico] 484009 Distrito Federal [State: Mexico] 484010 Durango [State: Mexico] 484011 Guanajuato [State: Mexico] 484012 Guerrero [State: Mexico] 484013 Hidalgo [State: Mexico] 484014 Jalisco [State: Mexico] 484015 México [State: Mexico] 484016 Michoacán de Ocampo [State: Mexico] 484017 Morelos [State: Mexico] 484018 Nayarit [State: Mexico] 484019 Nuevo León [State: Mexico] 484020 Oaxaca [State: Mexico] 484021 Puebla [State: Mexico] 484022 Querétaro [State: Mexico] 484023 Quintana Roo [State: Mexico] 484024 San Luis Potosí [State: Mexico] 484025 Sinaloa [State: Mexico] 484026 Sonora [State: Mexico] 484027 Tabasco [State: Mexico] 484028 Tamaulipas [State: Mexico] 484029 Tlaxcala [State: Mexico] 484030 Veracruz de Ignacio de la Llave [State: Mexico] 484031 Yucatán [State: Mexico] 484032 Zacatecas [State: Mexico] 484097 Abroad [State: Mexico] 484098 Unknown [State: Mexico] 484099 NIU (not in universe) [State: Mexico] 496011 Ulaanbaatar [Province: Mongolia] 496021 Dornod [Province: Mongolia] 496022 Sukhbaatar [Province: Mongolia] 496023 Khentii [Province: Mongolia] 496041 Tuv [Province: Mongolia] 496043 Selenge [Province: Mongolia] 496044 Dornogobi [Province: Mongolia] 496045 Darkhan-Uul [Province: Mongolia] 496046 Umnugobi [Province: Mongolia] 496048 Dundgobi, Gobisumber [Province: Mongolia] 496061 Orkhon [Province: Mongolia] 496062 Uvurkhangai [Province: Mongolia] 496063 Bulgan [Province: Mongolia] 496064 Bayankhongor [Province: Mongolia] 496065 Arkhangai [Province: Mongolia] 496067 Khuvsgul [Province: Mongolia] 496081 Zavkhan [Province: Mongolia] 496082 Gobi-Altai [Province: Mongolia] 496083 Bayan-Ulgii [Province: Mongolia] 496084 Khovd [Province: Mongolia] 496085 Uvs [Province: Mongolia] 496097 Abroad [Province: Mongolia] 496099 NIU (not in universe) [Province: Mongolia] 104001 Kachin [State: Myanmar] 104002 Kayah [State: Myanmar] 104003 Kayin [State: Myanmar] 104004 Chin [State: Myanmar] 104005 Sagaing [State: Myanmar] 104006 Tanintharyi [State: Myanmar] 104007 Bago [State: Myanmar] 104008 Magway [State: Myanmar] 104009 Mandalay [State: Myanmar] 104010 Mon [State: Myanmar] 104011 Rakhine [State: Myanmar] 104012 Yangon [State: Myanmar] 104013 Shan [State: Myanmar] 104014 Ayeyawady [State: Myanmar] 104015 Nay Pyi Taw [State: Myanmar] 104097 Abroad [State: Myanmar] 104099 NIU [State: Myanmar] 591002 Coclé [Province: Panama] 591003 Colón, Comarca Kuna Yala (San Blas) [Province: Panama] 591004 Bocas de Toro, Chiriquí, Comarca Ngäbe Buglé, Veraguas [Province: Panama] 591005 Comarca Emberá, Darién [Province: Panama] 591006 Herrera [Province: Panama] 591007 Los Santos [Province: Panama] 591008 Panamá [Province: Panama] 591009 Unknown district in Panamá province [Province: Panama] 591097 Foreign country [Province: Panama] 591098 Unknown [Province: Panama] 591099 NIU (not in universe) [Province: Panama] 608001 Abra [Province: Philippines] 608002 Agusan del norte [Province: Philippines] 608003 Agusan del sur [Province: Philippines] 608004 Aklan [Province: Philippines] 608005 Albay [Province: Philippines] 608006 Antique [Province: Philippines] 608007 Basilan, City Of Isabela [Province: Philippines] 608008 Bataan [Province: Philippines] 608010 Batangas [Province: Philippines] 608011 Benguet [Province: Philippines] 608012 Bohol [Province: Philippines] 608013 Bukidnon [Province: Philippines] 608014 Bulacan [Province: Philippines] 608015 Cagayan, Batanes [Province: Philippines] 608016 Camarines norte [Province: Philippines] 608017 Camarines Sur [Province: Philippines] 608018 Camiguin [Province: Philippines] 608019 Capiz [Province: Philippines] 608020 Catanduanes [Province: Philippines] 608021 Cavite [Province: Philippines] 608022 Cebu [Province: Philippines] 608023 Davao (Davao del Norte) [Province: Philippines] 608024 Davao del Sur, Davao Occidental [Province: Philippines] 608025 Davao Oriental [Province: Philippines] 608026 Eastern Samar [Province: Philippines] 608027 Ifugao [Province: Philippines] 608028 Ilocos Norte [Province: Philippines] 608029 Ilocos Sur [Province: Philippines] 608030 Iloilo, Guimaras [Province: Philippines] 608031 Isabela [Province: Philippines] 608032 Kalinga-Apayao, Apayo, Kalinga [Province: Philippines] 608033 La Union [Province: Philippines] 608034 Laguna [Province: Philippines] 608035 Lanao del Norte [Province: Philippines] 608036 Lanao del Sur, Maguindanao, Marawi City and Cotabato city [Province: Philippines] 608037 Leyte, Biliran [Province: Philippines] 608039 Manila [Province: Philippines] 608040 Marinduque [Province: Philippines] 608041 Masbate [Province: Philippines] 608042 Misamis Occidental [Province: Philippines] 608043 Misamis Oriental [Province: Philippines] 608044 Mountain Province [Province: Philippines] 608045 Negros Occidental [Province: Philippines] 608046 Negros Oriental [Province: Philippines] 608047 Cotabato (North Cotabato) [Province: Philippines] 608048 Northern Samar [Province: Philippines] 608049 Nueva Ecija [Province: Philippines] 608050 Nueva Vizcaya [Province: Philippines] 608051 Occidental Mindoro [Province: Philippines] 608052 Oriental Mindoro [Province: Philippines] 608053 Palawan [Province: Philippines] 608054 Pampanga [Province: Philippines] 608055 Pangasinan [Province: Philippines] 608056 Quezon [Province: Philippines] 608057 Quirino [Province: Philippines] 608058 Rizal [Province: Philippines] 608059 Romblon [Province: Philippines] 608060 Samar (Western Samar) [Province: Philippines] 608061 Siquijor [Province: Philippines] 608062 Sorsogon [Province: Philippines] 608063 South Cotabato, Sarangani [Province: Philippines] 608064 Southern Leyte [Province: Philippines] 608065 Sultan Kudarat [Province: Philippines] 608066 Sulu [Province: Philippines] 608067 Surigao Del Norte, Dinagat islands [Province: Philippines] 608068 Surigao del Sur [Province: Philippines] 608069 Tarlac [Province: Philippines] 608070 Tawi-Tawi [Province: Philippines] 608071 Zambales [Province: Philippines] 608072 Zamboanga Norte [Province: Philippines] 608073 Zamboanga del Sur, Zamboanga Sibugay [Province: Philippines] 608074 Manila Metro, 2nd District [Province: Philippines] 608075 Manila Metro, 3rd District [Province: Philippines] 608076 Manila Metro, 4th District [Province: Philippines] 608077 Aurora [Province: Philippines] 608097 Foreign country [Province: Philippines] 608098 Unknown [Province: Philippines] 608099 NIU (not in universe) [Province: Philippines] 642001 Alba [County: Romania] 642002 Arad [County: Romania] 642003 Arges [County: Romania] 642004 Bacau [County: Romania] 642005 Bihor [County: Romania] 642006 Bistrita Nasaud [County: Romania] 642007 Botosani [County: Romania] 642008 Brasov [County: Romania] 642009 Braila [County: Romania] 642010 Buzau [County: Romania] 642011 Caras Severin [County: Romania] 642012 Cluj [County: Romania] 642013 Constanta [County: Romania] 642014 Covasna [County: Romania] 642015 Dambovita [County: Romania] 642016 Dolj [County: Romania] 642017 Galati [County: Romania] 642018 Gorj [County: Romania] 642019 Harghita [County: Romania] 642020 Hunedoara [County: Romania] 642022 Iasi [County: Romania] 642024 Maramures [County: Romania] 642025 Mehedinti [County: Romania] 642026 Mures [County: Romania] 642027 Neamt [County: Romania] 642028 Olt [County: Romania] 642029 Prahova [County: Romania] 642030 Satu Mare [County: Romania] 642031 Salaj [County: Romania] 642032 Sibiu [County: Romania] 642033 Suceava [County: Romania] 642034 Teleorman [County: Romania] 642035 Timis [County: Romania] 642036 Tulcea [County: Romania] 642037 Vaslui [County: Romania] 642038 Valcea [County: Romania] 642039 Vrancea [County: Romania] 642043 Bucharest Sector 1 to 6 [County: Romania] 642051 Calarasi, Giurgiu, Ialomita, Ilfov [County: Romania] 642097 Foreign country [County: Romania] 642098 Unknown [County: Romania] 642099 NIU (not in universe) [County: Romania] 646002 Byumba, Kigali Ngali, Kigali Ville, Kibungo, Umutara [Province: Rwanda] 646003 Gitarama [Province: Rwanda] 646004 Butare [Province: Rwanda] 646005 Gikongoro [Province: Rwanda] 646006 Cyangugu [Province: Rwanda] 646007 Kibuye [Province: Rwanda] 646008 Gisenyi [Province: Rwanda] 646009 Ruhengeri [Province: Rwanda] 646097 Foreign Countries [Province: Rwanda] 646098 Unknown [Province: Rwanda] 646099 NIU [Province: Rwanda] 705001 Pomurska [Region: Slovenia] 705002 Podravska [Region: Slovenia] 705003 Koroška [Region: Slovenia] 705004 Savinjska [Region: Slovenia] 705005 Zasavska [Region: Slovenia] 705006 Spodnjeposavska [Region: Slovenia] 705007 Jugovzhodna Slovenija [Region: Slovenia] 705008 Osrednjeslovenska [Region: Slovenia] 705009 Gorenjska [Region: Slovenia] 705010 Notranjsko-kraška [Region: Slovenia] 705011 Goriška [Region: Slovenia] 705012 Obalno-kraška [Region: Slovenia] 705097 Abroad [Region: Slovenia] 705999 NIU (not in universe) [Region: Slovenia] 710001 Western Cape [Province: South Africa] 710004 Free State [Province: South Africa] 710005 Eastern Cape, KwaZulu-Natal [Province: South Africa] 710007 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape [Province: South Africa] 710097 Foreign country [Province: South Africa] 710098 Unknown [Province: South Africa] 710099 NIU (not in universe) [Province: South Africa] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Abroad [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 740001 Paramaribo [District: Suriname] 740002 Wanica [District: Suriname] 740003 Nickerie [District: Suriname] 740005 Saramacca, Coronie [District: Suriname] 740006 Marowijne, Commewijne [District: Suriname] 740008 Brokopondo, Para [District: Suriname] 740010 Sipaliwini [District: Suriname] 740096 Suriname, district unknown [District: Suriname] 740097 Foreign [District: Suriname] 740098 Unknown [District: Suriname] 764010 Bangkok [Province: Thailand] 764011 Samut Prakan [Province: Thailand] 764012 Nonthaburi [Province: Thailand] 764013 Pathum Thani [Province: Thailand] 764014 Phra Nakhon Si Ayutthaya [Province: Thailand] 764015 Ang Thong [Province: Thailand] 764016 Lop Buri [Province: Thailand] 764017 Sing Buri [Province: Thailand] 764018 Chai Nat [Province: Thailand] 764019 Sa Kaeo, Prachin Buri [Province: Thailand] 764020 Chon Buri [Province: Thailand] 764021 Rayong [Province: Thailand] 764022 Chanthaburi [Province: Thailand] 764023 Trat [Province: Thailand] 764024 Chachoengsao [Province: Thailand] 764026 Nakhon Nayok [Province: Thailand] 764027 Saraburi [Province: Thailand] 764030 Nakhon Ratchasima [Province: Thailand] 764031 Buri Ram [Province: Thailand] 764032 Surin [Province: Thailand] 764033 Si Sa Ket [Province: Thailand] 764034 Ubon Ratchathani, Yasothon, Amnat Charoen [Province: Thailand] 764036 Chaiyaphum [Province: Thailand] 764039 Nong Bua Lam Phu, Udon Thani [Province: Thailand] 764040 Khon Kaen [Province: Thailand] 764042 Loei [Province: Thailand] 764043 Nong Khai [Province: Thailand] 764044 Maha Sarakham [Province: Thailand] 764045 Roi Et [Province: Thailand] 764046 Kalasin [Province: Thailand] 764047 Sakon Nakhon [Province: Thailand] 764048 Nakhon Phanom, Mukdahan [Province: Thailand] 764050 Chiang Mai [Province: Thailand] 764051 Lamphun [Province: Thailand] 764052 Lampang [Province: Thailand] 764053 Uttaradit [Province: Thailand] 764054 Phrae [Province: Thailand] 764055 Nan [Province: Thailand] 764057 Phayao, Chiang Rai [Province: Thailand] 764058 Mae Hong Son [Province: Thailand] 764060 Nakhon Sawan [Province: Thailand] 764061 Uthai Thani [Province: Thailand] 764062 Kamphaeng Phet [Province: Thailand] 764063 Tak [Province: Thailand] 764064 Sukhothai [Province: Thailand] 764065 Phitsanulok [Province: Thailand] 764066 Phichit [Province: Thailand] 764067 Phetchabun [Province: Thailand] 764070 Ratchaburi [Province: Thailand] 764071 Kanchanaburi [Province: Thailand] 764072 Suphanburi [Province: Thailand] 764073 Nakhon Pathom [Province: Thailand] 764074 Samut Sakhon [Province: Thailand] 764075 Samut Songkhram [Province: Thailand] 764076 Phetchaburi [Province: Thailand] 764077 Prachuap Khiri Khan [Province: Thailand] 764080 Nakhon Si Thammarat [Province: Thailand] 764082 Phangnga [Province: Thailand] 764083 Phuket [Province: Thailand] 764084 Krabi, Surat Thani [Province: Thailand] 764086 Ranong, Chumphon [Province: Thailand] 764090 Songkhla [Province: Thailand] 764091 Satun [Province: Thailand] 764092 Trang [Province: Thailand] 764093 Phatthalung [Province: Thailand] 764094 Pattani [Province: Thailand] 764095 Yala [Province: Thailand] 764096 Narathiwat [Province: Thailand] 764097 Same province [Province: Thailand] 764098 Unknown province, but within Thaliand [Province: Thailand] 764997 Abroad [Province: Thailand] 764998 Unknown [Province: Thailand] 764999 NIU (not in universe) [Province: Thailand] 768001 Maritime, Lomé [Region: Togo] 768002 Plateaux, Centrale, Kara [Region: Togo] 768003 Savanes [Region: Togo] 768097 Foreign Country [Region: Togo] 768098 Unknown [Region: Togo] 768099 NIU [Region: Togo] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 800101 Kalangala [District: Uganda] 800102 Kampala [District: Uganda] 800103 Kiboga, Kyankwanzi [District: Uganda] 800104 Luwero, Nakasongola, Nakaseke [District: Uganda] 800105 Masaka, Ssembabule, Bukomansimbi, Kalungu, Lwengo [District: Uganda] 800106 Mpigi, Wakiso, Butambala, Gomba [District: Uganda] 800107 Mubende, Mityana [District: Uganda] 800108 Mukono, Kayunga, Buikwe, Buvuma [District: Uganda] 800110 Rakai, Lyantonde [District: Uganda] 800201 Bugiri, Iganga, Mayuge, Namutumba, Luuka, Namayingo [District: Uganda] 800202 Busia, Tororo, Butaleja [District: Uganda] 800204 Jinja [District: Uganda] 800205 Kamuli, Kaliro, Buyende [District: Uganda] 800206 Kapchorwa, Bukwo, Kween [District: Uganda] 800207 Katakwi, Soroti, Kaberamaido, Amuria, Serere [District: Uganda] 800208 Kumi, Bukedea, Ngora [District: Uganda] 800209 Mbale, Sironko, Bududa, Manafwa, Bulambuli [District: Uganda] 800210 Pallisa, Budaka, Kibuku [District: Uganda] 800301 Adjumani, Moyo [District: Uganda] 800302 Apac, Oyam, Kole [District: Uganda] 800303 Arua, Yumbe, Koboko, Maracha [District: Uganda] 800304 Gulu, Amuru, Nwoya, Omoro [District: Uganda] 800305 Kitgum, Pader, Agago, Lamwo [District: Uganda] 800306 Kotido, Moroto, Nakapiripirit, Abim, Kaabong, Amudat, Napak [District: Uganda] 800307 Lira, Amolatar, Dokolo, Alebtong, Otuke [District: Uganda] 800310 Nebbi, Zombo [District: Uganda] 800401 Bundibugyo, Ntoroko [District: Uganda] 800402 Bushenyi, Mbarara, Ntungamo, Ibanda, Isingiro, Kiruhura, Buhweju, Mitooma, Rubirizi, Sheema [District: Uganda] 800403 Hoima [District: Uganda] 800404 Kabale, Rubanda [District: Uganda] 800405 Kabarole, Kamwenge, Kyenjojo, Kyegegwa [District: Uganda] 800406 Kasese [District: Uganda] 800407 Kibaale, Kagadi, Kakumiro [District: Uganda] 800408 Kisoro [District: Uganda] 800409 Masindi, Buliisa, Kiryandongo [District: Uganda] 800412 Rukungiri, Kanungu [District: Uganda] 800096 Visitor [District: Uganda] 800097 Foreign country [District: Uganda] 800098 Unknown [District: Uganda] 804001 The Autonomous Republic of Crimea [Region: Ukraine] 804005 Vinnytska oblast [Region: Ukraine] 804007 Volynska oblast [Region: Ukraine] 804012 Dnipropetrovska oblast [Region: Ukraine] 804014 Donetska oblast [Region: Ukraine] 804018 Zhytomyrska oblast [Region: Ukraine] 804021 Zakarpatska oblast [Region: Ukraine] 804023 Zaporizka oblast [Region: Ukraine] 804026 Ivano-Frankivska oblast [Region: Ukraine] 804032 Kyivska oblast [Region: Ukraine] 804035 Kirovohradska oblast [Region: Ukraine] 804044 Luhanska oblast [Region: Ukraine] 804046 Lvivska oblast [Region: Ukraine] 804048 Mykolaivska oblast [Region: Ukraine] 804051 Odeska oblast [Region: Ukraine] 804053 Poltavska oblast [Region: Ukraine] 804056 Rivnenska oblast [Region: Ukraine] 804059 Sumska oblast [Region: Ukraine] 804061 Ternopilska oblast [Region: Ukraine] 804063 Kharkivska oblast [Region: Ukraine] 804065 Khersonska oblast [Region: Ukraine] 804068 Khmelnytska oblast [Region: Ukraine] 804071 Cherkaska oblast [Region: Ukraine] 804073 Chernivetska oblast [Region: Ukraine] 804074 Chernihivska oblast [Region: Ukraine] 804080 Kyiv (independent city) [Region: Ukraine] 804085 Sevastopol (independent city) [Region: Ukraine] 804097 Foreign country [Region: Ukraine] 804098 Unknown [Region: Ukraine] 804099 NIU (not in universe) [Region: Ukraine] 858001 Montevideo [Department: Uruguay] 858002 Artigas [Department: Uruguay] 858003 Canelones [Department: Uruguay] 858004 Cerro Largo [Department: Uruguay] 858005 Colonia [Department: Uruguay] 858006 Durazno [Department: Uruguay] 858007 Flores [Department: Uruguay] 858008 Florida [Department: Uruguay] 858009 Lavalleja [Department: Uruguay] 858010 Maldonado [Department: Uruguay] 858011 Paysandú [Department: Uruguay] 858012 Río Negro [Department: Uruguay] 858013 Rivera [Department: Uruguay] 858014 Rocha [Department: Uruguay] 858015 Salto [Department: Uruguay] 858016 San Jose [Department: Uruguay] 858017 Soriano [Department: Uruguay] 858018 Tacuarembó [Department: Uruguay] 858019 Treinta Y Tres [Department: Uruguay] 858097 Abroad [Department: Uruguay] 858098 Unknown [Department: Uruguay] 858999 NIU (not in universe) [Department: Uruguay] 862001 Federal District, Vargas [State: Venezuela] 862002 Amazonas Federal Territory [State: Venezuela] 862003 Anzoátegui [State: Venezuela] 862004 Apure [State: Venezuela] 862005 Aragua [State: Venezuela] 862007 Bolívar [State: Venezuela] 862008 Carabobo [State: Venezuela] 862009 Cojedes [State: Venezuela] 862010 Amacuros Delta Federal Territory [State: Venezuela] 862011 Falcón [State: Venezuela] 862012 Guárico [State: Venezuela] 862013 Lara [State: Venezuela] 862014 Barinas, Mérida [State: Venezuela] 862015 Miranda [State: Venezuela] 862016 Monagas [State: Venezuela] 862017 Nueva Esparta, Federal Dependencies [State: Venezuela] 862018 Portuguesa [State: Venezuela] 862019 Sucre [State: Venezuela] 862020 Táchira [State: Venezuela] 862021 Trujillo [State: Venezuela] 862022 Yaracuy [State: Venezuela] 862023 Zulia [State: Venezuela] 862097 Foreign country [State: Venezuela] 862098 Unknown [State: Venezuela] 862099 NIU (not in universe) [State: Venezuela] Migration: Global Variables -- PERSON Years residing in current locality MIGYRS1 indicates how many years the person has resided in their current locality of residence. 00 Less than 1 year 01 1 year (or 1 year or less) 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95+ years 96 Less than 5 years 97 More than 5 years 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON State of previous residence, Myanmar; consistent boundaries, GIS MIG1_P_MM indicates the person's state of previous residence within Myanmar. The person may have moved at any time in their life. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 104001 Kachin 104002 Kayah 104003 Kayin 104004 Chin 104005 Sagaing 104006 Tanintharyi 104007 Bago 104008 Magway 104009 Mandalay 104010 Mon 104011 Rakhine 104012 Yangon 104013 Shan 104014 Ayeyawady 104015 Nay Pyi Taw 104097 Abroad 104099 NIU Migration: F-N Variables -- PERSON District of previous residence, Myanmar; consistent boundaries, GIS MIG2_P_MM indicates the person's province of previous residence within Myanmar. The migration could have occurred at any time in the past. Migration province codes from MIG2_P_MM are compatible with codes from GEO2_MM. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 104001001 Myitkyina 104001002 Mohnyin 104001003 Bhamo 104001004 Putao 104002001 Loikaw 104002002 Bawlakhe 104003001 Hpa-An 104003002 Pharpon 104003003 Myawady 104003004 Kawkareik 104004001 Haka 104004002 Falam 104004003 Mindat 104005001 Sagaing 104005002 Shwebo 104005003 Monywa 104005004 Katha 104005005 Kalay 104005006 Tamu 104005007 Mawlaik 104005008 Hkamti 104005009 Yinmarpin 104006001 Dawei 104006002 Myeik 104006003 Kawthoung 104007001 Bago 104007002 Toungoo 104007003 Pyay 104007004 Thayawady 104008001 Magway 104008002 Minbu 104008003 Thayet 104008004 Pakokku 104008005 Gangaw 104009001 Mandalay 104009002 Pyin Oo Lwin 104009003 Kyaukse 104009004 Myingyan 104009005 Nyaung U 104009006 Yame`Thin 104009007 Meiktila 104010001 Mawlamyine 104010002 Thaton 104011001 Sittway 104011002 Myauk U 104011003 Maungtaw 104011004 Kyaukpyu 104011005 Thandwe 104012001 North Yangon 104012002 East Yangon 104012003 South Yangon 104012004 West Yangon 104013001 Taunggyi 104013002 Loilin 104013003 Linkhe` 104013004 Lashio 104013005 Muse 104013006 Kyaukme 104013007 Kunlon 104013008 Laukine 104013009 Hopan 104013010 Makman 104013011 Kengtung 104013012 Minesat 104013013 Tachileik 104013014 Minephyat 104013099 Shan region, district unknown 104014001 Pathein 104014002 Phyapon 104014003 Maubin 104014004 Myaungmya 104014005 Labutta 104014006 Hinthada 104015001 Ottara (North) 104015002 Dekkhina (South) 104015099 Nay Pyi Taw state, district unknown 104097097 Abroad 104099099 NIU Migration: F-N Variables -- PERSON Disability status DISABLED indicates whether the person reported a disability of any kind. 0 NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown Disability Variables -- PERSON Employment disability DISEMP indicates if the respondent was economically inactive because of disabilities or, in some instances, other health-related reasons. 1 Disabled 2 Not disabled 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Blind or vision-impaired DISBLND indicates whether the person was blind or had limited vision. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Deaf or hearing-impaired DISDEAF indicates whether the person was deaf or had limited hearing. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Disability limiting ability to walk DISMOBIL indicates whether the person has difficulty walking or climbing stairs. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Mental disability DISMNTL indicates whether the person suffered a mental disability in the form of diminished capacity. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Difficulty remembering or concentrating (Washington group) WGCOGN indicates the person's level of difficulty in remembering or concentrating. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty hearing (Washington group) WGHEAR indicates the person's level of difficulty in hearing, even if using a hearing aid. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty walking or climbing stairs (Washington group) WGMOBIL indicates the person's level of difficulty in walking or climbing stairs. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty seeing (Washington group) WGVISION indicates the person's level of difficulty in seeing, even while wearing glasses. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Person number (within household) Myanmar 2014: All records This variable indicates the person number within the household. 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 Technical Person Variables -- PERSON Relationship <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">3. Relationship to the head of the household</span><div class="i1">[] 1. Head of household<br />[] 2. Spouse<br />[] 3. Son / daughter<br />[] 4. Son / daughter-in-law<br />[] 5. Grandchild / great grandchild<br />[] 6. Parent / parent-in-Law<br />[] 7. Sibling<br />[] 8. Grandparent<br />[] 9. Other relative<br />[] 10. Adopted child<br />[] 11. Non relative</div> <span class="h3">Part 2: For all Members of the Household</span></p> <p><span class="em">Question 3: Relationship to head of the household</span></p> <p>108. Once you have established the head of a household, mark her/his relationship as [1] "Head" in question 3. Then establish the relationship of each person in the household to this head. As you write the names of household members in column 2, mark relationship in column 3 and Sex in column 4 at the same time. You will realize that in most cases you will be using the relationship to the head, sex and birth order of children to fill-in column 2.</p> <p>109. For example: for head of household, mark "[1]" in column 2 and if female then mark [2] in column 4. Then mark the relationship of each person to the head of household as given in the code list.</p> <p><span class="pg">[p. 25]</span></p> <p>110. Before you record the information you should find out whether or not the child identified as 'son' or 'daughter' is the head's biological child. If he/she is not, establish further whether he/she falls under [10] - adopted child, [4] -son/daughter in law, [9] -other-relative or [11] - non-relative. This must be done for each child and person in the household.</p> <p>111. There may be instances where there are several persons who are not related by blood or marriage but who are still members of the same household. These are more likely to occur in urban areas. Take the eldest person or if they are all the same age then make the one who coordinators activities in the house like paying rent, bills, etc. or the person who moved in the dwelling first and invited the rest. Record him/her as "head" [1] and the rest as "non-relative" [11]. There may be many such cases in Yangon or major cities/towns where more than one unrelated person (such as students) may be living in a conventional household. This may also be applicable in the government staff quarters for the single persons.</p> <p>112. Note that the head of household can be a male or a female. In some places, you will find a woman as the head of the household. Do not always imagine that the head of household must be a man. If the household head is a woman, code appropriately and include the relationships of other household members to her. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates the person's relationship with the household head. 01 Head of household 02 Spouse 03 Son or daughter 04 Son or daughter-in-law 05 Grandchild or great-grandchild 06 Parent or parent-in-law 07 Sibling 08 Grandparent 09 Other relative 10 Adopted child 11 Non relative 99 NIU (not in universe) Demographic Variables -- PERSON Sex <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">4. Sex</span><div class="i1">[] 1. Male<br />[] 2. Female</div> <span class="h3">Part 2: For all Members of the Household</span></p> <p><span class="em">Question 4: Sex</span></p> <p>113. Ask "what is the sex of [the respondent]? This must be done for each household member. Then mark "1" if male or "2" if female. It is always important to ask about the sex of a person even where this may be obvious. All persons must be classified by sex. Be sure to ask the sex of all persons who are not visible to you since there may be names that can refer to either sex.</p> <p>114. Check that the sex is compatible with relationship and name; do not assign "female" to persons shown as "spouse" when the head is a female and vice-versa. Also, take particular attention to mark the sex of very young children correctly. Often you will not know whether a baby carried on its mother's back is a boy or a girl. In such cases, you must ask, do not guess. You should ensure that everybody's sex is recorded. Blanks are strictly forbidden. Myanmar 2014: All persons This variable indicates the person's sex. 1 Male 2 Female Demographic Variables -- PERSON Age <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">5. Completed age</span>_ _</p> <div class="i1">If age greater than or equal to 98, write "98". If less than one write "00".</div> <span class="h3">Part 2: For all Members of the Household</span></p> <p><span class="em">Question 5: Age in completed years</span></p> <p>116. Ask "what is the age of [the respondent] in completed years?". Write the age in completed years (two digits) in the boxes provided. Age in completed years means the person's age at his/hers last birthday. Always start by asking the person's age and follow up with the question on the date of birth as a consistency check on the former. For babies under one year of age, write 00. Use two digits in recording age, e.g. "01","02", etc. Persons aged 98 years and over should be coded "98". Make sure always that your writing is legible and write only within the boxes.</p> <p>117. Be careful not to round ages up to the next birthday. In Myanmar, it is common to report the coming age rather than completed age. A child who is aged four years and 11 months should for example be entered as "04" and not "05". When recording age you must confirm carefully that it is completed age.</p> <p>118. It is also possible that some respondents will give you the year when they were born based on the Myanmar year. You must verify if the year given is in normal English year or Myanmar year. A conversion table has been prepared so that if any respondent gives the age in Myanmar year so that you can check the corresponding age in English and record accordingly. Age in the census must be filled in English year.</p> <p>119. The column on age must not be left blank. Some people may not know their ages. If a person's age is not known, you must make the best estimate possible. There are various ways in which you can estimate a person's age. Sometimes, people have documents such as religious certificates, birth registration certificates, identity card which shows the year of the birth, "Household Registration List" with date of birth of each member (in case you were given the Household Listing") in which case it is easy to calculate age. Use such information to get correct information on age.</p> <p><span class="pg">[p. 26]</span></p> <p>120. Generally, it is not so easy to estimate age for members of the household if none of them know their age. When you come across a household where all members do not know their ages. In such cases concentrate first on establishing the age of one or two persons in the household. One reliable age may help in working out the ages of others whether they are older or younger and by how many years.</p> <p>121. It is sometimes possible to estimate a person's age by relating his/her birth to some notable historical event. With these instructions is a Calendar of Events, which lists the dates of major events in the history of Myanmar. If the person can remember how old he/she was at the time at the event, you can work out the person's age.</p> <p>122. This is how to use the calendar of events to estimate the respondent's age.</p> <div class="i1">a) Ask for any historical event, which occurred around the time of the birth/childhood of the respondent.<br />b) Ask how old the respondent was when that event occurred or how many years elapsed before his/her birth.<br />c) Then use this information to work out his/her age. For example, if respondent was about 3 years when the U Thant Conflict happened in Myanmar. First, check which year U Thant conflict happened and, it is in 1973 according to English year and 1334 in Myanmar year. When we check the current age of a person born in 1973 from the table, it is 40 years. So this person should be 3 + 43 = 46 years at the time of the census in 2014. You can use the same approach to establish the age of a person in the household. If this method fails, you should try the following approach.</div><p>123. Simply estimate how old he/she may be.</p> <div class="i1">a) Then select from the list of historical events, some events which occurred about the time when according to your estimate he/she must have been born.<br />b) Ask whether he/she has heard about any of those events.<br />c) If he/she has, ask him/her to give you an indication of how old he/she was when this event occurred or how many years elapsed before he/she was born.<br />d) Then, from this information work out his/her age.</div><p>124. If this still fails, then base your estimate on biological relationships. For instance, a woman who does not know her age but who has two or three children of her own is unlikely to be less than 15 years old, however, small she may look. You may then try to work out her age by the following methods.</p> <div class="i1">a) Determine the age of her eldest child.<br />b) Ask her to give an estimate of her age at the birth of this child. However, without further probing, you should not base your assumption on the eldest child who is presently living. There is the likelihood that in certain cases, the first child died or that the woman had miscarriages or stillbirths. Therefore, if the woman tells you that she had one miscarriage or stillbirth before the oldest living child was born, you should make your estimation from the year of the first miscarriage/stillbirth or livebirth.</div><p>125. When you have arrived at the best estimate you can make of a person's age, check that it is compatible with his or her relationship to others in the household. Obviously, children cannot be older than their parents, women seldom marry before they are 15 years old and men before they are 18 years old, and so on.</p> <p>[p. 27-29 contain a figure titled "Table 2: Historical Calendar of Events in Myanmar/Current". The figure has been omitted.]</p> <p>126. For a person who remembers the year of birth or through checking the "Household Registration List" if voluntarily given and upon getting the date of birth; you can, use the Age Conversion Table (Figure 3) to get his/her age at the time of the census. For example, if a person was born in 1960. According to this table, he/she will be 53 years old.</p> <div class="i1">Any estimate of age, however rough, is better than a response of "don't know". Do the best you can to report ages accurately.</div> Myanmar 2014: All persons This variable indicates the person's age. 00 Under 1 year old 01 1 year 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90+ Demographic Variables -- PERSON Marital status <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">6. Marital Status</span><div class="i1">[] 1. Single (never married)<br />[] 2. Married<br />[] 3. Widowed<br />[] 4. Divorced / separated<br />[] 5. Renounced</div> <span class="h3">Part 2: For all Members of the Household</span></p> <p><span class="em">Question 6: Marital Status</span></p> <p>127. Ask the question "What is [the respondent]'s marital status?" and mark the option corresponding to the person's answer. Note that respondents are not required to provide proof of their marital union, but you are required to record the answer given.</p> <p>128. The category "5 Renounced" applies mainly to Monks, Nuns and "Yawgi". You must mark "1" for all persons who have never been married. This includes all children who have not yet reached the age of marriage. Do not ask this question to people below the age of 10 years; just record option "1" for them. Myanmar 2014: All persons This variable indicates the person's marital status. 1 Single (never married) 2 Married 3 Widowed 4 Divorced or separated 5 Renounced Demographic Variables -- PERSON Disability seeing <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">9. Disability: does [the respondent] have any difficulty...?</span><div class="i1"><span class="em">i. Seeing, even if wearing glasses</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ ii. Hearing, even if using hearing aid</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iii. Walking, climbing steps, carrying items</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iv. Remembering or concentrating</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div> <span class="h3">Disability section</span></p> <p>137. Disability serves as an umbrella term for impairments, activity limitations or participation restrictions (ICF, 2005). While it is desirable to collect information on all aspects of disability, this aim cannot be achieved in censuses or even in surveys not dedicated to disability. However, tge census can be used to obtain data on selected aspects of disability.</p> <p>138. Disability can be measured for a variety of purposes. Each purpose can be related to different dimensions of disability or different conceptual components of disability. Hence, there is a need for a clear link between the purpose of measurement and the operationalization of the indicators of disability.</p> <p>139. In order to collect disability information, the questions to identify persons who are at greater risk than the general population of experiencing restrictions in performing complex activities (such as activities of daily living) or participating in roles (such as working) if no support were accorded to them. Measurements intended to identify this 'at risk' population represent the most basic end of the spectrum of activities (i.e. activities such as walking, remembering, seeing, hearing). This 'at risk' group would include persons with limitations in basic activities who may or may not also experience limitations in more complex activities and/or restrictions in participation. This in turn may depend on whether or not they use assistive devices or have a supportive environment.</p> <p>140. The questions on disability ask about difficulties the person may have when doing certain activities, because of a health or other problem.</p> <div class="i1">Objective: The purpose of the introduction is to get the respondent to focus on difficulties they may have that are the result of some physical or mental health problem. Since persons living in developing countries may not have access to modern medicine, which would provide a diagnosed 'condition', the term problem was substituted. However, the term "condition" can be interchangeably used with the term "problem" if that facilitates the respondent understanding the context. We are interested in establishing difficulties that occur within a health or social life context rather than those caused by a lack of resources.<br />Definitions: Health refers to the general condition of the body or mind with reference to soundness, vitality, and freedom from disease. Problem refers to the respondent's perception of a departure from physical, mental or emotional well-being. This includes specific health problems such as a disease or chronic condition, a missing limb, organ, or any type of impairment. It also includes more vague disorders not always thought of as health-related such as senility, depression, retardation, drug dependency, accidental injuries, etc.</div><p>141. Ask "does [the respondent] have difficulty seeing, even if wearing glasses?"</p> <div class="i1">1. No - no difficulty<br />2. Yes - some difficulty<br />3. Yes - a lot of difficulty<br />4. Cannot do at <br />all<br />Objective: The purpose of this question is to identify persons who have vision difficulties or problems of any kind even when wearing glasses (if they wear glasses). They can have a problem seeing things close up or far away. They may not be able to see out of one eye or they may be only able to see directly in front of them, but not to the sides. Any difficulty with vision that they consider a problem should be captured. <br />Definition/s: Seeing refers to an individual using his/her eyes and visual capacity in order to perceive or observe what is happening around them. <br />Instructions: Note if the person is wearing glasses and make sure that they understand that the question refers to difficulties they may have while they are wearing their glasses. <br />The answer categories are set up so that the respondent can indicate 'yes', 'no' or that they cannot do it easily. However people aren't always sure how much difficulty is considered to be enough for a 'yes' answer. So they usually qualify their 'yes' with comments about their experience such as 'yes', I have a little problem or 'yes sometimes', or, when the problem is very serious, they indicate 'Oh, yes, a lot' answer categories try to capture that process. They may have to be repeated for the first one or two questions in order for the respondent to get familiar with the choices. The choices are same for the four questions on disability.</div> Myanmar 2014: All persons This variable indicates the degree of difficulty or disability that the person has seeing, even if wearing glasses. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot see at all Disability Variables -- PERSON Disability hearing <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">9. Disability: does [the respondent] have any difficulty...?</span><div class="i1"><span class="em">i. Seeing, even if wearing glasses</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ ii. Hearing, even if using hearing aid</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iii. Walking, climbing steps, carrying items</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iv. Remembering or concentrating</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div> <span class="h3">Disability section</span></p> <p>137. Disability serves as an umbrella term for impairments, activity limitations or participation restrictions (ICF, 2005). While it is desirable to collect information on all aspects of disability, this aim cannot be achieved in censuses or even in surveys not dedicated to disability. However, tge census can be used to obtain data on selected aspects of disability.</p> <p>138. Disability can be measured for a variety of purposes. Each purpose can be related to different dimensions of disability or different conceptual components of disability. Hence, there is a need for a clear link between the purpose of measurement and the operationalization of the indicators of disability.</p> <p>139. In order to collect disability information, the questions to identify persons who are at greater risk than the general population of experiencing restrictions in performing complex activities (such as activities of daily living) or participating in roles (such as working) if no support were accorded to them. Measurements intended to identify this 'at risk' population represent the most basic end of the spectrum of activities (i.e. activities such as walking, remembering, seeing, hearing). This 'at risk' group would include persons with limitations in basic activities who may or may not also experience limitations in more complex activities and/or restrictions in participation. This in turn may depend on whether or not they use assistive devices or have a supportive environment.</p> <p>140. The questions on disability ask about difficulties the person may have when doing certain activities, because of a health or other problem.</p> <div class="i1">Objective: The purpose of the introduction is to get the respondent to focus on difficulties they may have that are the result of some physical or mental health problem. Since persons living in developing countries may not have access to modern medicine, which would provide a diagnosed 'condition', the term problem was substituted. However, the term "condition" can be interchangeably used with the term "problem" if that facilitates the respondent understanding the context. We are interested in establishing difficulties that occur within a health or social life context rather than those caused by a lack of resources.<br />Definitions: Health refers to the general condition of the body or mind with reference to soundness, vitality, and freedom from disease. Problem refers to the respondent's perception of a departure from physical, mental or emotional well-being. This includes specific health problems such as a disease or chronic condition, a missing limb, organ, or any type of impairment. It also includes more vague disorders not always thought of as health-related such as senility, depression, retardation, drug dependency, accidental injuries, etc.</div><p>142. Ask "Does [the respondent] have difficulty hearing, even if using a hearing aid?"</p> <div class="i1">1. No- no difficulty<br />2. Yes - some difficulty<br />3. Yes - a lot of difficulty<br />4. Cannot do at all<br />Objective: The purpose of this question to identify persons who have some hearing limitation or problems of any kind with their hearing even when using a hearing aid (if they wear a hearing aid). They can have a problem hearing only when they are in a noisy environment, or they may have problems distinguishing sounds from different sources. They may not be able to hear in one ear or both. Any difficulty with hearing that they consider a problem should be captured. <br />Definition/s: Hearing refers to an individual using his/her ears and auditory (or hearing) capacity in order to know what is being said to them or the sounds of activity, including danger that is happening around them. <br />Instructions: Note if the person is wearing hearing aids, make sure that they understand that the question refers to difficulties they may have even while they are wearing their hearing aids.</div> Myanmar 2014: All persons This variable indicates the degree of difficulty or disability that the person has hearing, even if using hearing aids. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot hear at all Disability Variables -- PERSON Disability walking <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">9. Disability: does [the respondent] have any difficulty...?</span><div class="i1"><span class="em">i. Seeing, even if wearing glasses</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ ii. Hearing, even if using hearing aid</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iii. Walking, climbing steps, carrying items</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iv. Remembering or concentrating</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div> <span class="h3">Disability section</span></p> <p>137. Disability serves as an umbrella term for impairments, activity limitations or participation restrictions (ICF, 2005). While it is desirable to collect information on all aspects of disability, this aim cannot be achieved in censuses or even in surveys not dedicated to disability. However, tge census can be used to obtain data on selected aspects of disability.</p> <p>138. Disability can be measured for a variety of purposes. Each purpose can be related to different dimensions of disability or different conceptual components of disability. Hence, there is a need for a clear link between the purpose of measurement and the operationalization of the indicators of disability.</p> <p>139. In order to collect disability information, the questions to identify persons who are at greater risk than the general population of experiencing restrictions in performing complex activities (such as activities of daily living) or participating in roles (such as working) if no support were accorded to them. Measurements intended to identify this 'at risk' population represent the most basic end of the spectrum of activities (i.e. activities such as walking, remembering, seeing, hearing). This 'at risk' group would include persons with limitations in basic activities who may or may not also experience limitations in more complex activities and/or restrictions in participation. This in turn may depend on whether or not they use assistive devices or have a supportive environment.</p> <p>140. The questions on disability ask about difficulties the person may have when doing certain activities, because of a health or other problem.</p> <div class="i1">Objective: The purpose of the introduction is to get the respondent to focus on difficulties they may have that are the result of some physical or mental health problem. Since persons living in developing countries may not have access to modern medicine, which would provide a diagnosed 'condition', the term problem was substituted. However, the term "condition" can be interchangeably used with the term "problem" if that facilitates the respondent understanding the context. We are interested in establishing difficulties that occur within a health or social life context rather than those caused by a lack of resources.<br />Definitions: Health refers to the general condition of the body or mind with reference to soundness, vitality, and freedom from disease. Problem refers to the respondent's perception of a departure from physical, mental or emotional well-being. This includes specific health problems such as a disease or chronic condition, a missing limb, organ, or any type of impairment. It also includes more vague disorders not always thought of as health-related such as senility, depression, retardation, drug dependency, accidental injuries, etc.</div><p>143. Ask "does [the respondent] have difficulty walking or climbing steps or lifting objects or gripping?"</p> <div class="i1">a. No- no difficulty<br />b. Yes - some difficulty<br />c. Yes - a lot of difficulty<br />d. Cannot do at all<br />Objective: The purpose of this question is to identify persons who have some limitation or problems of any kind getting around on foot or lifting items by hand. It may or may not contribute to difficulty in doing their daily activities. They can have a problem walking more than a block, or short or long distances, or the problem can be that they can't walk up or down steps without difficulty. They may not be able to walk any distance without stopping to rest or they may not be able to walk without using some type of device such as a cane, a walker or crutches. In some instances, they may be unable to stand for more than a minute or two and need a wheelchair to get from place to place. Difficulties walking can include those resulting from impairments in balance, endurance, or other non-musculoskeletal systems. Any difficulty with walking (whether it is on flat land or up or down steps) that they consider a problem should be captured. <br />Definition/s: Walking refers to an individual using his/her legs in such a way as to propel themselves over the ground to get from point A to point B. The capacity to walk should be without assistance of any device or human. If such assistance is needed, the person has difficulty walking.</div> Myanmar 2014: All persons This variable indicates the degree of difficulty or disability that the person has walking, climbing steps, and/or carrying items. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot walk at all Disability Variables -- PERSON Disability remembering <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">9. Disability: does [the respondent] have any difficulty...?</span><div class="i1"><span class="em">i. Seeing, even if wearing glasses</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ ii. Hearing, even if using hearing aid</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iii. Walking, climbing steps, carrying items</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div><div class="i1"><span class="em">_ iv. Remembering or concentrating</span></div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes a lot of difficulty<br />[] 4. Cannot do at all</div> <span class="h3">Disability section</span></p> <p>137. Disability serves as an umbrella term for impairments, activity limitations or participation restrictions (ICF, 2005). While it is desirable to collect information on all aspects of disability, this aim cannot be achieved in censuses or even in surveys not dedicated to disability. However, tge census can be used to obtain data on selected aspects of disability.</p> <p>138. Disability can be measured for a variety of purposes. Each purpose can be related to different dimensions of disability or different conceptual components of disability. Hence, there is a need for a clear link between the purpose of measurement and the operationalization of the indicators of disability.</p> <p>139. In order to collect disability information, the questions to identify persons who are at greater risk than the general population of experiencing restrictions in performing complex activities (such as activities of daily living) or participating in roles (such as working) if no support were accorded to them. Measurements intended to identify this 'at risk' population represent the most basic end of the spectrum of activities (i.e. activities such as walking, remembering, seeing, hearing). This 'at risk' group would include persons with limitations in basic activities who may or may not also experience limitations in more complex activities and/or restrictions in participation. This in turn may depend on whether or not they use assistive devices or have a supportive environment.</p> <p>140. The questions on disability ask about difficulties the person may have when doing certain activities, because of a health or other problem.</p> <div class="i1">Objective: The purpose of the introduction is to get the respondent to focus on difficulties they may have that are the result of some physical or mental health problem. Since persons living in developing countries may not have access to modern medicine, which would provide a diagnosed 'condition', the term problem was substituted. However, the term "condition" can be interchangeably used with the term "problem" if that facilitates the respondent understanding the context. We are interested in establishing difficulties that occur within a health or social life context rather than those caused by a lack of resources.<br />Definitions: Health refers to the general condition of the body or mind with reference to soundness, vitality, and freedom from disease. Problem refers to the respondent's perception of a departure from physical, mental or emotional well-being. This includes specific health problems such as a disease or chronic condition, a missing limb, organ, or any type of impairment. It also includes more vague disorders not always thought of as health-related such as senility, depression, retardation, drug dependency, accidental injuries, etc.</div><p>144. Ask "does [the respondent] have difficulty remembering or concentrating or learning?"</p> <div class="i1">1. No - no difficulty<br />2. Yes - some difficulty<br />3. Yes - a lot of difficulty<br />4. Cannot do at all<br />Objective: The purpose of this question is to identify persons who have some problems with remembering or thinking that contributes to difficulty in doing their daily activities. They can have a problem finding their way around, they can't concentrate on what they are doing, or they may forget where they are or what month it is. They may not remember what someone just said to them or they may seem confused or frightened about most things. Any difficulty with remembering, concentrating or understanding what is going on around them that they or family members (if the family member is the respondent) consider a problem should be captured. We do not intend to capture difficulties remembering or concentrating because of common everyday situations such as high workload or stress, or as a result of substance abuse. <br />Definition/s: Remembering refers to an individual using his/her memory capacity in order to recall what has happened around them. It means the individual can bring to mind or think again about something that has taken place in the past (either the recent past or further back). In connection with younger people, remembering is often associated with storing facts learned in school and being able to retrieve them when needed. Concentrating refers to an individual using his mental ability to accomplish some task such as reading, calculating numbers, learning something. It is associated with focusing on the task at hand in order to complete the task. It is the act of directing ones full attention to one subject or to focus without distraction on one thing.</div> Myanmar 2014: All persons This variable indicates the degree of difficulty or disability that the person has remembering or concentrating. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot remember/concentrate at all Disability Variables -- PERSON Identity card <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">10. Type of identity card</span><div class="i1">[] 1. Citizenship Scrutiny Card (pink)<br />[] 2. Associate Scrutiny Citizenship Card (blue)<br />[] 3. Naturalized Scrutiny Citizenship Card (green)<br />[] 4. National Registration Card (three fold card, green for men, pink for women)<br />[] 5. Religious Card<br />[] 6. Temporary Registration Card (white)<br />[] 7. Foreign Registration Card (FRC)<br />[] 8. Foreign Passport<br />[] 9. None of the documents above<br />[] 10. Child below 10 years</div> <span class="em">Question 10: Type of Identity Card</span></p> <p>145. Ask the question "what type of Identity Card do you hold?" The question is applicable to only those aged 10 years and above. For the people 9 years and below, mark code "10".</p> <p>146. Do not ask to see the identity card or any other documentation but if the person gives you her/his identity card then use it to code correctly. The options are seven for the different types of identity cards, and in addition there are three other options, namely:</p> <div class="i1">8. Foreign passport normal for foreigners<br />9. None of the documents yet 10 years and over<br />10. Child 9 years and below (not applicable)</div><p>147. Note that a person who is 10 years and over but does not have any of the cards from "1" to "8"should be marked as "9" i.e. none of the documents.</p> <p>148. A one-page sheet with different types of identity cards is provided to assist respondents who don't know the type or color of their cards. In case you come across a respondent who do not know the type of ID card they hold then show them the various types of all ID cards. Then he should be in a position to point the one each person holds, and you can code appropriately thereafter. Even those who may report that they have lost their ID card, ask them what type it was, then code accordingly.</p> <p><span class="pg">[p. 34]</span></p> <p>149. For children below 10 years, mark option "10 - not applicable". Reassure the respondents that you are not there to ensure that people hold any particular type of identity card. It will only be used to know the proportion of the population according to which type. And if the government should redouble its effort to provide people with more necessary cards; that is how many people don't hold cards at all. Myanmar 2014: Persons age 10+ [discrepancies: none] This variable indicates the type of identity card a person has. 0 NIU (not in universe) 1 Citizenship Scrutiny Card (pink) 2 Associate Scrutiny Card (blue) 3 Naturalised Scrutiny Card (green) 4 National Registration Card (3-fold) 5 Religious card 6 Temporary Registration Card (white) 7 Foreign Registration Card (FRC) 8 Foreign Passport 9 None Other Person Variables -- PERSON Region or state of birth <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h2">Place of birth</span></p> <p><span class="h3">11. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 11 and 12: Place of birth</span> <br />150. Ask "which Township was [the respondent] born?" Place of birth for the purpose of census is the usual place of residence (township) of the mother at the time of the person's birth.</p> <p>151. This question establishes persons who are not enumerated in their places of birth and hence have migrated. It will be used in estimating migration patterns. Sometimes expectant mothers move from the rural areas to urban areas for only purposes of delivery since maternity services are better at the latter. This kind of movement is short lived and must not be confused with a migratory one. Please note that birthplace does not mean place of delivery, but the usual place of residence of mother at the time of the respondent's birth. For example if a woman who usually resides in Nyaung Done township goes to a hospital in a township in Yangon to deliver her baby, the birthplace is Nyaung Done township and not the township in Yangon.</p> <p>152. For persons born in Myanmar, record Township code using the code list provided. For a person born in same township as where being enumerated write "000". Mark either "1" for urban or "2" for rural in question (12) accordingly. If the place of birth was in Ward it will correspond to urban and if village tract then mark as rural. For a person born outside Myanmar, code the country of birth using country code provided. Even for non-Myanmar citizens you must ask whether they were born in urban or rural areas and code accordingly.</p> <p>153. Urban/rural may have changed since birth. If so, record the status at the time of birth. Note if the respondent does not know the township, only the ward or village tract name of birth, you would then assign accordingly (ward = urban) ad (village tract = rural). Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates a person's state or region of birth. 01 Kachin 02 Kayah 03 Kayin 04 Chin 05 Sagaing 06 Tanintharyi 07 Bago 08 Magway 09 Mandalay 10 Mon 11 Rakhine 12 Yangon 13 Shan 14 Ayeyawady 15 Nay Pyi Taw 16 Outside Myanmar 99 NIU (not in universe) Nativity and Birthplace Variables -- PERSON District of birth <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h2">Place of birth</span></p> <p><span class="h3">11. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 11 and 12: Place of birth</span> <br />150. Ask "which Township was [the respondent] born?" Place of birth for the purpose of census is the usual place of residence (township) of the mother at the time of the person's birth.</p> <p>151. This question establishes persons who are not enumerated in their places of birth and hence have migrated. It will be used in estimating migration patterns. Sometimes expectant mothers move from the rural areas to urban areas for only purposes of delivery since maternity services are better at the latter. This kind of movement is short lived and must not be confused with a migratory one. Please note that birthplace does not mean place of delivery, but the usual place of residence of mother at the time of the respondent's birth. For example if a woman who usually resides in Nyaung Done township goes to a hospital in a township in Yangon to deliver her baby, the birthplace is Nyaung Done township and not the township in Yangon.</p> <p>152. For persons born in Myanmar, record Township code using the code list provided. For a person born in same township as where being enumerated write "000". Mark either "1" for urban or "2" for rural in question (12) accordingly. If the place of birth was in Ward it will correspond to urban and if village tract then mark as rural. For a person born outside Myanmar, code the country of birth using country code provided. Even for non-Myanmar citizens you must ask whether they were born in urban or rural areas and code accordingly.</p> <p>153. Urban/rural may have changed since birth. If so, record the status at the time of birth. Note if the respondent does not know the township, only the ward or village tract name of birth, you would then assign accordingly (ward = urban) ad (village tract = rural). Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates a person's district of birth. 0101 Myitkyina 0102 Mohnyin 0103 Bhamo 0104 Putao 0201 Loikaw 0202 Bawlakhe 0301 Hpa-An 0302 Pharpon 0303 Myawady 0304 Kawkareik 0401 Haka 0402 Falam 0403 Mindat 0501 Sagaing 0502 Shwebo 0503 Monywa 0504 Katha 0505 Kalay 0506 Tamu 0507 Mawlaik 0508 Hkamti 0509 Yinmarpin 0601 Dawei 0602 Myeik 0603 Kawthoung 0701 Bago 0702 Toungoo 0703 Pyay 0704 Thayawady 0801 Magway 0802 Minbu 0803 Thayet 0804 Pakokku 0805 Gangaw 0901 Mandalay 0902 Pyin Oo Lwin 0903 Kyaukse 0904 Myingyan 0905 Nyaung U 0906 Yame'Thin 0907 Meiktila 1001 Mawlamyine 1002 Thaton 1101 Sittway 1102 Myauk U 1103 Maungtaw 1104 Kyaukpyu 1105 Thandwe 1201 North Yangon 1202 East Yangon 1203 South Yangon 1204 West Yangon 1301 Taunggyi 1302 Loilin 1303 Linkhe' 1304 Lashio 1305 Muse 1306 Kyaukme 1307 Kunlon 1308 Laukine 1309 Hopan 1310 Makman 1311 Kengtung 1312 Minesat 1313 Tachileik 1314 Minephyat 1399 Shan region, district unknown 1401 Pathein 1402 Phyapon 1403 Maubin 1404 Myaungmya 1405 Labutta 1406 Hinthada 1501 Ottara (North) 1502 Dekkhina (South) 1604 Outside Myanmar 9999 NIU (not in universe) Nativity and Birthplace Variables -- PERSON Township or country of birth <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h2">Place of birth</span></p> <p><span class="h3">11. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 11 and 12: Place of birth</span> <br />150. Ask "which Township was [the respondent] born?" Place of birth for the purpose of census is the usual place of residence (township) of the mother at the time of the person's birth.</p> <p>151. This question establishes persons who are not enumerated in their places of birth and hence have migrated. It will be used in estimating migration patterns. Sometimes expectant mothers move from the rural areas to urban areas for only purposes of delivery since maternity services are better at the latter. This kind of movement is short lived and must not be confused with a migratory one. Please note that birthplace does not mean place of delivery, but the usual place of residence of mother at the time of the respondent's birth. For example if a woman who usually resides in Nyaung Done township goes to a hospital in a township in Yangon to deliver her baby, the birthplace is Nyaung Done township and not the township in Yangon.</p> <p>152. For persons born in Myanmar, record Township code using the code list provided. For a person born in same township as where being enumerated write "000". Mark either "1" for urban or "2" for rural in question (12) accordingly. If the place of birth was in Ward it will correspond to urban and if village tract then mark as rural. For a person born outside Myanmar, code the country of birth using country code provided. Even for non-Myanmar citizens you must ask whether they were born in urban or rural areas and code accordingly.</p> <p>153. Urban/rural may have changed since birth. If so, record the status at the time of birth. Note if the respondent does not know the township, only the ward or village tract name of birth, you would then assign accordingly (ward = urban) ad (village tract = rural). Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates a person's township of birth. 010101 Myitkyina 010102 Waingmaw 010103 Ingyanyan 010104 Tanaing 010105 Chiphwe 010106 Hsotlaw 010151 Hsinbo (Sub- township) 010152 Hsadone (Sub- township) 010153 Kanpaikti (Sub- township) 010154 Shinbwayyan (Sub- township) 010155 Panwa (Sub- township) 010201 Mohnyin 010202 Mogaung 010203 Phakant 010251 Hopin (Sub- township) 010252 Kamine (Sub- township) 010301 Bhamo 010302 Shwegu 010303 Momauk 010304 Mansi 010351 Myohla (Sub- township) 010352 Lwe'Ge' (Sub- township) 010353 Dotphoneyan (Sub- township) 010401 Putao 010402 Sumprabum 010403 Machanbaw 010404 Khaunglanphoo 010405 Naungmoon 010451 Pannandin (Sub- township) 020101 Loikaw 020102 Dimawso 020103 Phruso 020104 Shardaw 020201 Bawlakhe 020202 Parsaung 020203 Meisi 020251 Ywathit (Sub- township) 030101 Hpa-An 030102 Hlaingbwe 030103 Thandaunggyi 030151 Paingkyon (Sub- township) 030152 Shan Ywathit (Sub- township) 030153 Leiktho (Sub- township) 030154 Bawgali (Sub- township) 030201 Pharpon 030251 Kamamaung (Sub- township) 030301 Myawady 030351 Sugali (Sub- township) 030352 Wawlaymyaing (Sub- township) 030401 Kawkareik 030402 Kyarinseikkyi 030451 Payarthonezu (Sub- township) 030452 Kyaidon (Sub- township) 040101 Haka 040102 Thantlang 040201 Falam 040202 Tedim 040203 Tonzaung 040251 Rihkhuadal (Sub- township) 040252 Cikha (Sub- township) 040301 Mindat 040302 Matupi 040303 Kanpalet 040304 Paletwa 040351 Reazu (Sub- township) 040352 Sami (Sub- township) 050101 Sagaing 050102 Myinmu 050103 Myaung 050201 Shwebo 050202 Khin U 050203 Wetlet 050204 Kambalu 050205 Kyunhla 050206 Ye U 050207 Depayin 050208 Tasei 050251 Kyaukmyaung (Sub- township) 050301 Monywa 050302 Butalin 050303 Ayartaw 050304 Chaungoo 050401 Katha 050402 Indaw 050403 Tigyaing 050404 Banmauk 050405 Kawlin 050406 Wuntho 050407 Pinlebu 050501 Kalay 050502 Kalewa 050503 Mingin 050601 Tamu 050651 Myothit (Sub- township) 050652 Khampat (Sub- township) 050701 Mawlaik 050702 Phaungpyin 050801 Hkamti 050802 Homalin 050803 Leshi 050804 Lahe 050805 Nanyun 050851 Mobaingluk (Sub- township) 050852 Sonemara (Sub- township) 050853 Htanparkway (Sub- township) 050854 Pansaung (Sub- township) 050855 Donhee (Sub- township) 050901 Yinmarpin 050902 Salingyi 050903 Palae 050904 Kani 060101 Dawei 060102 Lounglon 060103 Thayetchaung 060104 Yebyu 060151 Myitta (Sub- township) 060152 Kaleinaung (Sub- township) 060201 Myeik 060202 Kyunsu 060203 Palaw 060204 Tanintharyi 060251 Palauk (Sub- township) 060301 Kawthoung 060302 Bokepyin 060351 Khamaukkyi (Sub- township) 060352 Pyigyimandaing 060353 Karathuri (Sub- township) 070101 Bago 070102 Tanatpin 070103 Kawa 070104 Waw 070105 Nyaunglebin 070106 Kyauktaga 070107 Daik U 070108 Shwegyin 070201 Toungoo 070202 Yaedashe 070203 Kyaukkyi 070204 Pyu 070205 Oatwin 070206 Htantapin 070301 Pyay 070302 Paukkhaung 070303 Padaung 070304 Paunde 070305 Thegon 070306 Shwedaung 070401 Thayawady 070402 Letpadan 070403 Minhla 070404 Okpo 070405 Zigon 070406 Nattalin 070407 Monyo 070408 Gyobingauk 080101 Magway 080102 Yenangyoung 080103 Chauk 080104 Taungdwingyi 080105 Myothit 080106 Natmauk 080201 Minbu 080202 Pwintphyu 080203 Ngape 080204 Salin 080205 Saytottara 080301 Thayet 080302 Minhla 080303 Mindon 080304 Kamma 080305 Aunglan 080306 Sinpaungwe' 080401 Pakokku 080402 Yesagyo 080403 Myaing 080404 Pauk 080405 Seikphyu 080501 Gangaw 080502 Htilin 080503 Saw 080551 Kyaukhtu (Sub- township) 090101 Aungmyetharzan 090102 Chanayetharzan 090103 Mahaaungmye 090104 Chanmyatharzi 090105 Pyigyidagun 090106 Amarapura 090107 Patheingyi 090201 Pyinoolwin 090202 Madaya 090203 Sinku 090204 Mogok 090205 Thabeikkyin 090251 Tagaung (Sub- township) 090301 Kyaukse 090302 Singaing 090303 Myitthar 090304 Tada U 090401 Myingyan 090402 Taungtha 090403 Natogyi 090404 Kyaukpadaung 090405 Ngazun 090501 Nyaung U 090551 Ngathayauk (Sub- township) 090601 Yame'Thin 090602 Pyawbwe 090701 Meiktila 090702 Mahlaing 090703 Thazi 090704 Wundwin 100101 Mawlamyine 100102 Kyaikemaraw 100103 Chaungzon 100104 Thanbyuzayat 100105 Mudon 100106 Ye 100151 Lamine (Sub- township) 100152 Khawzar (Sub- township) 100201 Thaton 100202 Paung 100203 Kyaikto 100204 Bilin 110101 Sittway 110102 Ponnagyun 110103 Pauktaw 110104 Yathedaung 110201 Myauk U 110202 Kyauktaw 110203 Minbya 110204 Myebon 110301 Maungtaw 110302 Buthidaung 110351 Taungpyoletwe (Sub- township) 110401 Kyaukpyu 110402 Mannaung 110403 Yanbye 110404 An 110501 Thandwe 110502 Toungup 110503 Gwa 110551 Maei (Sub- township) 110552 Kyeintali (Sub- township) 120101 Insein 120102 Mingaladon 120103 Hmawby 120104 Hlegu 120105 Taikkyi 120106 Htantabin 120107 Shwepyitha 120108 Hlinethaya 120201 Thingangyun 120202 Yankin 120203 South Okkalapa 120204 North Okkalapa 120205 Thakayta 120206 Dawbon 120207 Tamway 120208 Pazuntaung 120209 Botahtaung 120210 Dagon Myothit (South) 120211 Dagon Myothit (North) 120212 Dagon Myothit (East) 120213 Dagon Myothit (Seikkan) 120214 Mingalataungnyunt 120301 Thanlyin 120302 Kyauktan 120303 Thongwa 120304 Khayan 120305 Twantay 120306 Kawhmu 120307 Kungyangon 120308 Dala 120309 Seikkyi/ Khanaungto 120310 Cocogyun 120351 Tada (Sub- township) 120401 Kyauktada 120402 Pabedan 120403 Lanmadaw 120404 Latha 120405 Ahlon 120406 Kyimyindine 120407 Sangyoung 120408 Hline 120409 Kamayut 120410 Mayangon 120411 Dagon 120412 Bahan 120413 Seikkan 130101 Taunggyi 130102 Nyaungshwe 130103 Hopon 130104 Hsihseng 130105 Kalaw 130106 Pindaya 130107 Ywarngan 130108 Yatsauk 130109 Pinlaung 130110 Phekon 130151 Kyauktalongyi (Sub- township) 130152 Indaw (Sub- township) 130153 Naungtayar (Sub- township) 130201 Loilem 130202 Le'Char 130203 Nanhsam (South) 130204 Kunhing 130205 Kehsi 130206 Mongkai 130207 Mineshu 130251 Panglong (Sub- township) 130252 Kholan (Sub- township) 130253 Karli (Sub- township) 130254 Minenaung (Sub- township) 130255 Minesan (Monsan) (Sub- township) 130301 Linkhe' 130302 Mone' 130303 Maukme' 130304 Minepan 130351 Homane (Sub- township) 130352 Kengtaung (Sub- township) 130401 Lashio 130402 Theinni 130403 Mineye' 130404 Tantyan 130501 Muse 130502 Namkham 130503 Kukai 130551 Monekoe (Sub- township) 130552 Manhero (Sub- township) 130553 Pansai (Kyukute) (Sub- township) 130554 Tamoenye (Sub- township) 130601 Kyaukme 130602 Naungkhio 130603 Hsipaw 130604 Namtu 130605 Namsan (North) 130606 Momeik 130607 Mabane 130608 Manton 130651 Minengaw (Sub- township) 130652 Minelon (Sub- township) 130701 Kunlon 130801 Laukine 130802 Kongyan 130851 Chinshwehaw (Sub- township) 130852 Mawhtike (Sub- township) 130901 Hopan 130952 Panlon (Sub- township) 131001 Makman 131051 Mankan (Sub- township) 131101 Kengtung 131102 Minekat 131103 Mineyan 131104 Minelar 131151 Mine Pauk (Sub- township) 131201 Minesat 131202 Minepyin 131203 Minetung 131251 Minekoke (Sub- township) 131252 Tontar (Sub- township) 131253 Ponparkyin (Sub- township) 131254 Monehta (Sub- township) 131301 Tachileik 131351 Talay (Sub- township) 131352 Kenglat (Sub- township) 131401 Minephyat 131402 Mineyaung 131451 Mineyu (Sub- township) 139999 Shan region, township unknown 140101 Kangyidaunt 140102 Kyaungon 140103 Kyonpyaw 140104 Ngaputaw 140105 Pathein 140106 Yekyi 140107 Thapaung 140151 Ngayokaung (Sub- township) 140152 Hainggyikyun (Sub- township) 140153 Shwethaungyan (Sub- township) 140154 Ngwehsaung (Sub- township) 140155 Ngathaingchaung (Sub- township) 140201 Kyaiklatt 140202 Daydaye 140203 Phyapon 140204 Bogale 140251 Ahmar (Sub- township) 140301 Nyaungdon 140302 Danubyu 140303 Pantanaw 140304 Maubin 140401 Myaungmya 140402 Wakema 140403 Einme 140501 Mawlamyinegyun 140502 Labutta 140551 Pyinsalu (Sub- township) 140601 Kyangin 140602 Zalun 140603 Myanaung 140604 Laymyethna 140605 Hinthada 140606 Ingapu 150101 Tatkon 150102 Zeyarthiri 150103 Ottarathiri 150104 Pobbathiri 150201 Pyinmana 150202 Lewe 150203 Zabuthiri 150204 Dekkhinathiri 160415 Thailand 160416 Malaysia 160419 Singapore 160420 China 160421 Japan 160422 South Korea 160423 India 160424 Bangladesh 160425 United States 160428 Other 999999 NIU (not in universe) Nativity and Birthplace Variables -- PERSON Born in urban or rural area <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h2">Place of birth</span></p> <p><span class="h3">12. Urban or rural</span><div class="i1">[] 1. Urban<br />[] 2. Rural</div> <span class="em">Questions 11 and 12: Place of birth</span> <br />150. Ask "which Township was [the respondent] born?" Place of birth for the purpose of census is the usual place of residence (township) of the mother at the time of the person's birth.</p> <p>151. This question establishes persons who are not enumerated in their places of birth and hence have migrated. It will be used in estimating migration patterns. Sometimes expectant mothers move from the rural areas to urban areas for only purposes of delivery since maternity services are better at the latter. This kind of movement is short lived and must not be confused with a migratory one. Please note that birthplace does not mean place of delivery, but the usual place of residence of mother at the time of the respondent's birth. For example if a woman who usually resides in Nyaung Done township goes to a hospital in a township in Yangon to deliver her baby, the birthplace is Nyaung Done township and not the township in Yangon.</p> <p>152. For persons born in Myanmar, record Township code using the code list provided. For a person born in same township as where being enumerated write "000". Mark either "1" for urban or "2" for rural in question (12) accordingly. If the place of birth was in Ward it will correspond to urban and if village tract then mark as rural. For a person born outside Myanmar, code the country of birth using country code provided. Even for non-Myanmar citizens you must ask whether they were born in urban or rural areas and code accordingly.</p> <p>153. Urban/rural may have changed since birth. If so, record the status at the time of birth. Note if the respondent does not know the township, only the ward or village tract name of birth, you would then assign accordingly (ward = urban) ad (village tract = rural). Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates if the person's place of birth was urban or rural. 1 Urban 2 Rural 9 NIU (not in universe) Nativity and Birthplace Variables -- PERSON Usual state of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of usual residence</span></p> <p><span class="h3">13. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 13 and 14: Place of usual residence</span></p> <p>154. Ask "which township does [the respondent] usual live?" A place of usual residence is where a person has lived for more than 6 months in the last 12 months, or where he/she intends to live for a longer time. For persons with usual residence in Myanmar, record Township code using the code list provided. If the place of usual residence is the same as township of enumeration write "000". If not, write the township 3 digit code. You are likely to find majority people will be enumerated at their usual place of residence. Also, ask if the place of usual residence is a ward or village tract then mark "1" or "2" as applicable.</p> <p>155. For persons with usual residence outside Myanmar, code the country of usual residence using code provided. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates a person's usual state or region of residence. 01 Kachin 02 Kayah 03 Kayin 04 Chin 05 Sagaing 06 Tanintharyi 07 Bago 08 Magway 09 Mandalay 10 Mon 11 Rakhine 12 Yangon 13 Shan 14 Ayeyawady 15 Nay Pyi Taw 16 Outside Myanmar 99 NIU (not in universe) Migration: Global Variables -- PERSON Usual district of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of usual residence</span></p> <p><span class="h3">13. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 13 and 14: Place of usual residence</span></p> <p>154. Ask "which township does [the respondent] usual live?" A place of usual residence is where a person has lived for more than 6 months in the last 12 months, or where he/she intends to live for a longer time. For persons with usual residence in Myanmar, record Township code using the code list provided. If the place of usual residence is the same as township of enumeration write "000". If not, write the township 3 digit code. You are likely to find majority people will be enumerated at their usual place of residence. Also, ask if the place of usual residence is a ward or village tract then mark "1" or "2" as applicable.</p> <p>155. For persons with usual residence outside Myanmar, code the country of usual residence using code provided. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates a person's usual district of residence. 0101 Myitkyina 0102 Mohnyin 0103 Bhamo 0104 Putao 0201 Loikaw 0202 Bawlakhe 0301 Hpa-An 0302 Pharpon 0303 Myawady 0304 Kawkareik 0401 Haka 0402 Falam 0403 Mindat 0501 Sagaing 0502 Shwebo 0503 Monywa 0504 Katha 0505 Kalay 0506 Tamu 0507 Mawlaik 0508 Hkamti 0509 Yinmarpin 0601 Dawei 0602 Myeik 0603 Kawthoung 0701 Bago 0702 Toungoo 0703 Pyay 0704 Thayawady 0801 Magway 0802 Minbu 0803 Thayet 0804 Pakokku 0805 Gangaw 0901 Mandalay 0902 Pyin Oo Lwin 0903 Kyaukse 0904 Myingyan 0905 Nyaung U 0906 Yame'Thin 0907 Meiktila 1001 Mawlamyine 1002 Thaton 1101 Sittway 1102 Myauk U 1103 Maungtaw 1104 Kyaukpyu 1105 Thandwe 1201 North Yangon 1202 East Yangon 1203 South Yangon 1204 West Yangon 1301 Taunggyi 1302 Loilin 1303 Linkhe' 1304 Lashio 1305 Muse 1306 Kyaukme 1307 Kunlon 1308 Laukine 1309 Hopan 1310 Makman 1311 Kengtung 1312 Minesat 1313 Tachileik 1314 Minephyat 1399 Shan region, district unknown 1401 Pathein 1402 Phyapon 1403 Maubin 1404 Myaungmya 1405 Labutta 1406 Hinthada 1501 Ottara (North) 1502 Dekkhina (South) 1503 Nay Pyi Taw region, district unknown 1604 Outside Myanmar 9999 NIU (not in universe) Migration: Global Variables -- PERSON Usual township or country of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of usual residence</span></p> <p><span class="h3">13. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 13 and 14: Place of usual residence</span></p> <p>154. Ask "which township does [the respondent] usual live?" A place of usual residence is where a person has lived for more than 6 months in the last 12 months, or where he/she intends to live for a longer time. For persons with usual residence in Myanmar, record Township code using the code list provided. If the place of usual residence is the same as township of enumeration write "000". If not, write the township 3 digit code. You are likely to find majority people will be enumerated at their usual place of residence. Also, ask if the place of usual residence is a ward or village tract then mark "1" or "2" as applicable.</p> <p>155. For persons with usual residence outside Myanmar, code the country of usual residence using code provided. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates a person's usual township or country of residence. 010101 Myitkyina 010102 Waingmaw 010103 Ingyanyan 010104 Tanaing 010105 Chiphwe 010106 Hsotlaw 010151 Hsinbo (Sub- township) 010152 Hsadone (Sub- township) 010153 Kanpaikti (Sub- township) 010154 Shinbwayyan (Sub- township) 010155 Panwa (Sub- township) 010201 Mohnyin 010202 Mogaung 010203 Phakant 010251 Hopin (Sub- township) 010252 Kamine (Sub- township) 010301 Bhamo 010302 Shwegu 010303 Momauk 010304 Mansi 010351 Myohla (Sub- township) 010352 Lwe'Ge' (Sub- township) 010353 Dotphoneyan (Sub- township) 010401 Putao 010402 Sumprabum 010403 Machanbaw 010404 Khaunglanphoo 010405 Naungmoon 010451 Pannandin (Sub- township) 020101 Loikaw 020102 Dimawso 020103 Phruso 020104 Shardaw 020201 Bawlakhe 020202 Parsaung 020203 Meisi 020251 Ywathit (Sub- township) 030101 Hpa-An 030102 Hlaingbwe 030103 Thandaunggyi 030151 Paingkyon (Sub- township) 030152 Shan Ywathit (Sub- township) 030153 Leiktho (Sub- township) 030154 Bawgali (Sub- township) 030201 Pharpon 030251 Kamamaung (Sub- township) 030301 Myawady 030351 Sugali (Sub- township) 030352 Wawlaymyaing (Sub- township) 030401 Kawkareik 030402 Kyarinseikkyi 030451 Payarthonezu (Sub- township) 030452 Kyaidon (Sub- township) 040101 Haka 040102 Thantlang 040201 Falam 040202 Tedim 040203 Tonzaung 040251 Rihkhuadal (Sub- township) 040252 Cikha (Sub- township) 040301 Mindat 040302 Matupi 040303 Kanpalet 040304 Paletwa 040351 Reazu (Sub- township) 040352 Sami (Sub- township) 050101 Sagaing 050102 Myinmu 050103 Myaung 050201 Shwebo 050202 Khin U 050203 Wetlet 050204 Kambalu 050205 Kyunhla 050206 Ye U 050207 Depayin 050208 Tasei 050251 Kyaukmyaung (Sub- township) 050301 Monywa 050302 Butalin 050303 Ayartaw 050304 Chaungoo 050401 Katha 050402 Indaw 050403 Tigyaing 050404 Banmauk 050405 Kawlin 050406 Wuntho 050407 Pinlebu 050501 Kalay 050502 Kalewa 050503 Mingin 050601 Tamu 050651 Myothit (Sub- township) 050652 Khampat (Sub- township) 050701 Mawlaik 050702 Phaungpyin 050801 Hkamti 050802 Homalin 050803 Leshi 050804 Lahe 050805 Nanyun 050851 Mobaingluk (Sub- township) 050852 Sonemara (Sub- township) 050853 Htanparkway (Sub- township) 050854 Pansaung (Sub- township) 050855 Donhee (Sub- township) 050901 Yinmarpin 050902 Salingyi 050903 Palae 050904 Kani 060101 Dawei 060102 Lounglon 060103 Thayetchaung 060104 Yebyu 060151 Myitta (Sub- township) 060152 Kaleinaung (Sub- township) 060201 Myeik 060202 Kyunsu 060203 Palaw 060204 Tanintharyi 060251 Palauk (Sub- township) 060301 Kawthoung 060302 Bokepyin 060351 Khamaukkyi (Sub- township) 060352 Pyigyimandaing 060353 Karathuri (Sub- township) 070101 Bago 070102 Tanatpin 070103 Kawa 070104 Waw 070105 Nyaunglebin 070106 Kyauktaga 070107 Daik U 070108 Shwegyin 070201 Toungoo 070202 Yaedashe 070203 Kyaukkyi 070204 Pyu 070205 Oatwin 070206 Htantapin 070301 Pyay 070302 Paukkhaung 070303 Padaung 070304 Paunde 070305 Thegon 070306 Shwedaung 070401 Thayawady 070402 Letpadan 070403 Minhla 070404 Okpo 070405 Zigon 070406 Nattalin 070407 Monyo 070408 Gyobingauk 080101 Magway 080102 Yenangyoung 080103 Chauk 080104 Taungdwingyi 080105 Myothit 080106 Natmauk 080201 Minbu 080202 Pwintphyu 080203 Ngape 080204 Salin 080205 Saytottara 080301 Thayet 080302 Minhla 080303 Mindon 080304 Kamma 080305 Aunglan 080306 Sinpaungwe' 080401 Pakokku 080402 Yesagyo 080403 Myaing 080404 Pauk 080405 Seikphyu 080501 Gangaw 080502 Htilin 080503 Saw 080551 Kyaukhtu (Sub- township) 090101 Aungmyetharzan 090102 Chanayetharzan 090103 Mahaaungmye 090104 Chanmyatharzi 090105 Pyigyidagun 090106 Amarapura 090107 Patheingyi 090201 Pyinoolwin 090202 Madaya 090203 Sinku 090204 Mogok 090205 Thabeikkyin 090251 Tagaung (Sub- township) 090301 Kyaukse 090302 Singaing 090303 Myitthar 090304 Tada U 090401 Myingyan 090402 Taungtha 090403 Natogyi 090404 Kyaukpadaung 090405 Ngazun 090501 Nyaung U 090551 Ngathayauk (Sub- township) 090601 Yame'Thin 090602 Pyawbwe 090701 Meiktila 090702 Mahlaing 090703 Thazi 090704 Wundwin 100101 Mawlamyine 100102 Kyaikemaraw 100103 Chaungzon 100104 Thanbyuzayat 100105 Mudon 100106 Ye 100151 Lamine (Sub- township) 100152 Khawzar (Sub- township) 100201 Thaton 100202 Paung 100203 Kyaikto 100204 Bilin 110101 Sittway 110102 Ponnagyun 110103 Pauktaw 110104 Yathedaung 110201 Myauk U 110202 Kyauktaw 110203 Minbya 110204 Myebon 110301 Maungtaw 110302 Buthidaung 110351 Taungpyoletwe (Sub- township) 110401 Kyaukpyu 110402 Mannaung 110403 Yanbye 110404 An 110501 Thandwe 110502 Toungup 110503 Gwa 110551 Maei (Sub- township) 110552 Kyeintali (Sub- township) 120101 Insein 120102 Mingaladon 120103 Hmawby 120104 Hlegu 120105 Taikkyi 120106 Htantabin 120107 Shwepyitha 120108 Hlinethaya 120201 Thingangyun 120202 Yankin 120203 South Okkalapa 120204 North Okkalapa 120205 Thakayta 120206 Dawbon 120207 Tamway 120208 Pazuntaung 120209 Botahtaung 120210 Dagon Myothit (South) 120211 Dagon Myothit (North) 120212 Dagon Myothit (East) 120213 Dagon Myothit (Seikkan) 120214 Mingalataungnyunt 120301 Thanlyin 120302 Kyauktan 120303 Thongwa 120304 Khayan 120305 Twantay 120306 Kawhmu 120307 Kungyangon 120308 Dala 120309 Seikkyi/ Khanaungto 120310 Cocogyun 120351 Tada (Sub- township) 120401 Kyauktada 120402 Pabedan 120403 Lanmadaw 120404 Latha 120405 Ahlon 120406 Kyimyindine 120407 Sangyoung 120408 Hline 120409 Kamayut 120410 Mayangon 120411 Dagon 120412 Bahan 120413 Seikkan 130101 Taunggyi 130102 Nyaungshwe 130103 Hopon 130104 Hsihseng 130105 Kalaw 130106 Pindaya 130107 Ywarngan 130108 Yatsauk 130109 Pinlaung 130110 Phekon 130151 Kyauktalongyi (Sub- township) 130152 Indaw (Sub- township) 130153 Naungtayar (Sub- township) 130201 Loilem 130202 Le'Char 130203 Nanhsam (South) 130204 Kunhing 130205 Kehsi 130206 Mongkai 130207 Mineshu 130251 Panglong (Sub- township) 130252 Kholan (Sub- township) 130253 Karli (Sub- township) 130254 Minenaung (Sub- township) 130255 Minesan (Monsan) (Sub- township) 130301 Linkhe' 130302 Mone' 130303 Maukme' 130304 Minepan 130351 Homane (Sub- township) 130352 Kengtaung (Sub- township) 130401 Lashio 130402 Theinni 130403 Mineye' 130404 Tantyan 130501 Muse 130502 Namkham 130503 Kukai 130551 Monekoe (Sub- township) 130552 Manhero (Sub- township) 130553 Pansai (Kyukute) (Sub- township) 130554 Tamoenye (Sub- township) 130601 Kyaukme 130602 Naungkhio 130603 Hsipaw 130604 Namtu 130605 Namsan (North) 130606 Momeik 130607 Mabane 130608 Manton 130651 Minengaw (Sub- township) 130652 Minelon (Sub- township) 130701 Kunlon 130801 Laukine 130802 Kongyan 130851 Chinshwehaw (Sub- township) 130852 Mawhtike (Sub- township) 130901 Hopan 130952 Panlon (Sub- township) 131001 Makman 131051 Mankan (Sub- township) 131101 Kengtung 131102 Minekat 131103 Mineyan 131104 Minelar 131201 Minesat 131202 Minepyin 131203 Minetung 131251 Minekoke (Sub- township) 131252 Tontar (Sub- township) 131253 Ponparkyin (Sub- township) 131254 Monehta (Sub- township) 131301 Tachileik 131351 Talay (Sub- township) 131352 Kenglat (Sub- township) 131401 Minephyat 131402 Mineyaung 131451 Mineyu (Sub- township) 139999 Shan region, township unknown 140101 Kangyidaunt 140102 Kyaungon 140103 Kyonpyaw 140104 Ngaputaw 140105 Pathein 140106 Yekyi 140107 Thapaung 140151 Ngayokaung (Sub- township) 140152 Hainggyikyun (Sub- township) 140153 Shwethaungyan (Sub- township) 140154 Ngwehsaung (Sub- township) 140155 Ngathaingchaung (Sub- township) 140201 Kyaiklatt 140202 Daydaye 140203 Phyapon 140204 Bogale 140251 Ahmar (Sub- township) 140301 Nyaungdon 140302 Danubyu 140303 Pantanaw 140304 Maubin 140401 Myaungmya 140402 Wakema 140403 Einme 140501 Mawlamyinegyun 140502 Labutta 140551 Pyinsalu (Sub- township) 140601 Kyangin 140602 Zalun 140603 Myanaung 140604 Laymyethna 140605 Hinthada 140606 Ingapu 150101 Tatkon 150102 Zeyarthiri 150103 Ottarathiri 150104 Pobbathiri 150201 Pyinmana 150202 Lewe 150203 Zabuthiri 150204 Dekkhinathiri 159999 Nay Pyi Taw region, township unknown 160415 Thailand 160416 Malaysia 160419 Singapore 160420 China 160423 India 160428 Other country 999999 NIU (not in universe) Migration: Global Variables -- PERSON Urban or rural usual residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of usual residence</span></p> <p><span class="h3">14. Urban or rural</span><div class="i1">[] 1. Urban<br />[] 2. Rural</div> <span class="em">Questions 13 and 14: Place of usual residence</span></p> <p>154. Ask "which township does [the respondent] usual live?" A place of usual residence is where a person has lived for more than 6 months in the last 12 months, or where he/she intends to live for a longer time. For persons with usual residence in Myanmar, record Township code using the code list provided. If the place of usual residence is the same as township of enumeration write "000". If not, write the township 3 digit code. You are likely to find majority people will be enumerated at their usual place of residence. Also, ask if the place of usual residence is a ward or village tract then mark "1" or "2" as applicable.</p> <p>155. For persons with usual residence outside Myanmar, code the country of usual residence using code provided. Myanmar 2014: Persons in conventional households [discrepancies: type I none; type II trace] This variable indicates if the person's usual place of residence is urban or rural. 1 Urban 2 Rural 8 Unknown 9 NIU (not in universe) Migration: Global Variables -- PERSON Duration of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of usual residence</span></p> <p><span class="h3">15. Duration in place of usual residence (in years)</span>_ _</p> <div class="i1">If less than 1 year write "00".</div> <span class="em">Question 15: Duration in place of usual residence (completed years)</span></p> <p>156. Ask "how many years has [the respondent] lived in current place of usual residence?" This is the number of years in completed years a person has lived in the township where he/she usual resides. This must be written in completed years. This is the number of years a person has been continuously living in this place without migration to other place for long periods.</p> <p>157. If the exact number of years is not known, try to estimate the number of years as you did for age of the respondent. If less than one year write "00". Kindly note that the visitors in a household will have their usual place of residence elsewhere and hence it should be asked with respect to that place</p> <p>158. For a person being enumerated in a township where he/she was born and have never moved, the number of years should be the same as their age since they have stayed in that township throughout their life. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates the duration of time (in years) a persons has lived in their usual place of residence. 00 Under 1 year 01 1 year 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90+ 99 NIU (not in universe) Migration: Global Variables -- PERSON Previous state of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of previous usual residence</span></p> <p><span class="h3">17. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 17 and 18: Place of previous usual residence</span></p> <p>162. Ask "where was [the respondent] previously living before moving to current usual place of residence? This question aims to establish how people have moved within the country. The question intends to capture the last previous place of usual residence. If the place of (last) previous residence is here (here = township of enumeration) write "000". Many persons stay in the same township. If not, write the township 3-digit code or if abroad the country of previous residence using the code list provided. Mark urban or rural in question 19 as appropriate and inquire the same to the respondent whose previous residence is abroad.</p> <p>For persons aged between 00 and 04 years (below 5 years old) the remaining parts of the questionnaire are not applicable hence their information ends here. The remaining questions should be left blank for children below 5 years of age. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates the person's previous state or region of residence. 01 Kachin 02 Kayah 03 Kayin 04 Chin 05 Sagaing 06 Tanintharyi 07 Bago 08 Magway 09 Mandalay 10 Mon 11 Rakhine 12 Yangon 13 Shan 14 Ayeyawady 15 Nay Pyi Taw 16 Outside Myanmar 99 NIU (not in universe) Migration: Global Variables -- PERSON Previous district of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of previous usual residence</span></p> <p><span class="h3">17. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 17 and 18: Place of previous usual residence</span></p> <p>162. Ask "where was [the respondent] previously living before moving to current usual place of residence? This question aims to establish how people have moved within the country. The question intends to capture the last previous place of usual residence. If the place of (last) previous residence is here (here = township of enumeration) write "000". Many persons stay in the same township. If not, write the township 3-digit code or if abroad the country of previous residence using the code list provided. Mark urban or rural in question 19 as appropriate and inquire the same to the respondent whose previous residence is abroad.</p> <p>For persons aged between 00 and 04 years (below 5 years old) the remaining parts of the questionnaire are not applicable hence their information ends here. The remaining questions should be left blank for children below 5 years of age. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates the person's previous district of residence. 0101 Myitkyina 0102 Mohnyin 0103 Bhamo 0104 Putao 0201 Loikaw 0202 Bawlakhe 0301 Hpa-An 0302 Pharpon 0303 Myawady 0304 Kawkareik 0401 Haka 0402 Falam 0403 Mindat 0501 Sagaing 0502 Shwebo 0503 Monywa 0504 Katha 0505 Kalay 0506 Tamu 0507 Mawlaik 0508 Hkamti 0509 Yinmarpin 0601 Dawei 0602 Myeik 0603 Kawthoung 0701 Bago 0702 Toungoo 0703 Pyay 0704 Thayawady 0801 Magway 0802 Minbu 0803 Thayet 0804 Pakokku 0805 Gangaw 0901 Mandalay 0902 Pyin Oo Lwin 0903 Kyaukse 0904 Myingyan 0905 Nyaung U 0906 Yame'Thin 0907 Meiktila 1001 Mawlamyine 1002 Thaton 1101 Sittway 1102 Myauk U 1103 Maungtaw 1104 Kyaukpyu 1105 Thandwe 1201 North Yangon 1202 East Yangon 1203 South Yangon 1204 West Yangon 1301 Taunggyi 1302 Loilin 1303 Linkhe' 1304 Lashio 1305 Muse 1306 Kyaukme 1307 Kunlon 1308 Laukine 1309 Hopan 1310 Makman 1311 Kengtung 1312 Minesat 1313 Tachileik 1314 Minephyat 1399 Shan region, district unknown 1401 Pathein 1402 Phyapon 1403 Maubin 1404 Myaungmya 1405 Labutta 1406 Hinthada 1501 Ottara (North) 1502 Dekkhina (South) 1503 Nay Pyi Taw state, district unknown 1604 Outside Myanmar 9999 NIU (not in universe) Migration: Global Variables -- PERSON Previous township or country of residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of previous usual residence</span></p> <p><span class="h3">17. Township</span>_ _ _</p> <div class="i1">If born here write "000". If not write township code, enter code from manual.</div> <span class="em">Questions 17 and 18: Place of previous usual residence</span></p> <p>162. Ask "where was [the respondent] previously living before moving to current usual place of residence? This question aims to establish how people have moved within the country. The question intends to capture the last previous place of usual residence. If the place of (last) previous residence is here (here = township of enumeration) write "000". Many persons stay in the same township. If not, write the township 3-digit code or if abroad the country of previous residence using the code list provided. Mark urban or rural in question 19 as appropriate and inquire the same to the respondent whose previous residence is abroad.</p> <p>For persons aged between 00 and 04 years (below 5 years old) the remaining parts of the questionnaire are not applicable hence their information ends here. The remaining questions should be left blank for children below 5 years of age. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates the person's previous township of residence. 010101 Myitkyina 010102 Waingmaw 010103 Ingyanyan 010104 Tanaing 010105 Chiphwe 010106 Hsotlaw 010151 Hsinbo (Sub-township) 010152 Hsadone (Sub-township) 010153 Kanpaikti (Sub-township) 010154 Shinbwayyan (Sub-township) 010155 Panwa (Sub-township) 010201 Mohnyin 010202 Mogaung 010203 Phakant 010251 Hopin (Sub-township) 010252 Kamine (Sub-township) 010301 Bhamo 010302 Shwegu 010303 Momauk 010304 Mansi 010351 Myohla (Sub-township) 010352 Lwe'Ge' (Sub-township) 010353 Dotphoneyan (Sub-township) 010401 Putao 010402 Sumprabum 010403 Machanbaw 010404 Khaunglanphoo 010405 Naungmoon 010451 Pannandin (Sub-township) 020101 Loikaw 020102 Dimawso 020103 Phruso 020104 Shardaw 020201 Bawlakhe 020202 Parsaung 020203 Meisi 020251 Ywathit (Sub-township) 030101 Hpa-An 030102 Hlaingbwe 030103 Thandaunggyi 030151 Paingkyon (Sub-township) 030152 Shan Ywathit (Sub-township) 030153 Leiktho (Sub-township) 030154 Bawgali (Sub-township) 030201 Pharpon 030251 Kamamaung (Sub-township) 030301 Myawady 030351 Sugali (Sub-township) 030352 Wawlaymyaing (Sub-township) 030401 Kawkareik 030402 Kyarinseikkyi 030451 Payarthonezu (Sub-township) 030452 Kyaidon (Sub-township) 040101 Haka 040102 Thantlang 040201 Falam 040202 Tedim 040203 Tonzaung 040251 Rihkhuadal (Sub-township) 040252 Cikha (Sub-township) 040301 Mindat 040302 Matupi 040303 Kanpalet 040304 Paletwa 040351 Reazu (Sub-township) 040352 Sami (Sub-township) 050101 Sagaing 050102 Myinmu 050103 Myaung 050201 Shwebo 050202 Khin U 050203 Wetlet 050204 Kambalu 050205 Kyunhla 050206 Ye U 050207 Depayin 050208 Tasei 050251 Kyaukmyaung (Sub-township) 050301 Monywa 050302 Butalin 050303 Ayartaw 050304 Chaungoo 050401 Katha 050402 Indaw 050403 Tigyaing 050404 Banmauk 050405 Kawlin 050406 Wuntho 050407 Pinlebu 050501 Kalay 050502 Kalewa 050503 Mingin 050601 Tamu 050651 Myothit (Sub-township) 050652 Khampat (Sub-township) 050701 Mawlaik 050702 Phaungpyin 050801 Hkamti 050802 Homalin 050803 Leshi 050804 Lahe 050805 Nanyun 050851 Mobaingluk (Sub-township) 050852 Sonemara (Sub-township) 050853 Htanparkway (Sub-township) 050854 Pansaung (Sub-township) 050855 Donhee (Sub-township) 050901 Yinmarpin 050902 Salingyi 050903 Palae 050904 Kani 060101 Dawei 060102 Lounglon 060103 Thayetchaung 060104 Yebyu 060151 Myitta (Sub-township) 060152 Kaleinaung (Sub-township) 060201 Myeik 060202 Kyunsu 060203 Palaw 060204 Tanintharyi 060251 Palauk (Sub-township) 060301 Kawthoung 060302 Bokepyin 060351 Khamaukkyi (Sub-township) 060352 Pyigyimandaing 060353 Karathuri (Sub-township) 070101 Bago 070102 Tanatpin 070103 Kawa 070104 Waw 070105 Nyaunglebin 070106 Kyauktaga 070107 Daik U 070108 Shwegyin 070201 Toungoo 070202 Yaedashe 070203 Kyaukkyi 070204 Pyu 070205 Oatwin 070206 Htantapin 070301 Pyay 070302 Paukkhaung 070303 Padaung 070304 Paunde 070305 Thegon 070306 Shwedaung 070401 Thayawady 070402 Letpadan 070403 Minhla 070404 Okpo 070405 Zigon 070406 Nattalin 070407 Monyo 070408 Gyobingauk 080101 Magway 080102 Yenangyoung 080103 Chauk 080104 Taungdwingyi 080105 Myothit 080106 Natmauk 080201 Minbu 080202 Pwintphyu 080203 Ngape 080204 Salin 080205 Saytottara 080301 Thayet 080302 Minhla 080303 Mindon 080304 Kamma 080305 Aunglan 080306 Sinpaungwe' 080401 Pakokku 080402 Yesagyo 080403 Myaing 080404 Pauk 080405 Seikphyu 080501 Gangaw 080502 Htilin 080503 Saw 080551 Kyaukhtu (Sub-township) 090101 Aungmyetharzan 090102 Chanayetharzan 090103 Mahaaungmye 090104 Chanmyatharzi 090105 Pyigyidagun 090106 Amarapura 090107 Patheingyi 090201 Pyinoolwin 090202 Madaya 090203 Sinku 090204 Mogok 090205 Thabeikkyin 090251 Tagaung (Sub-township) 090301 Kyaukse 090302 Singaing 090303 Myitthar 090304 Tada U 090401 Myingyan 090402 Taungtha 090403 Natogyi 090404 Kyaukpadaung 090405 Ngazun 090501 Nyaung U 090551 Ngathayauk (Sub-township) 090601 Yame'Thin 090602 Pyawbwe 090701 Meiktila 090702 Mahlaing 090703 Thazi 090704 Wundwin 100101 Mawlamyine 100102 Kyaikemaraw 100103 Chaungzon 100104 Thanbyuzayat 100105 Mudon 100106 Ye 100151 Lamine (Sub-township) 100152 Khawzar (Sub-township) 100201 Thaton 100202 Paung 100203 Kyaikto 100204 Bilin 110101 Sittway 110102 Ponnagyun 110103 Pauktaw 110104 Yathedaung 110201 Myauk U 110202 Kyauktaw 110203 Minbya 110204 Myebon 110301 Maungtaw 110302 Buthidaung 110351 Taungpyoletwe (Sub-township) 110401 Kyaukpyu 110402 Mannaung 110403 Yanbye 110404 An 110501 Thandwe 110502 Toungup 110503 Gwa 110551 Maei (Sub-township) 110552 Kyeintali (Sub-township) 120101 Insein 120102 Mingaladon 120103 Hmawby 120104 Hlegu 120105 Taikkyi 120106 Htantabin 120107 Shwepyitha 120108 Hlinethaya 120201 Thingangyun 120202 Yankin 120203 South Okkalapa 120204 North Okkalapa 120205 Thakayta 120206 Dawbon 120207 Tamway 120208 Pazuntaung 120209 Botahtaung 120210 Dagon Myothit (South) 120211 Dagon Myothit (North) 120212 Dagon Myothit (East) 120213 Dagon Myothit (Seikkan) 120214 Mingalataungnyunt 120301 Thanlyin 120302 Kyauktan 120303 Thongwa 120304 Khayan 120305 Twantay 120306 Kawhmu 120307 Kungyangon 120308 Dala 120309 Seikkyi/ Khanaungto 120310 Cocogyun 120351 Tada (Sub-township) 120401 Kyauktada 120402 Pabedan 120403 Lanmadaw 120404 Latha 120405 Ahlon 120406 Kyimyindine 120407 Sangyoung 120408 Hline 120409 Kamayut 120410 Mayangon 120411 Dagon 120412 Bahan 120413 Seikkan 130101 Taunggyi 130102 Nyaungshwe 130103 Hopon 130104 Hsihseng 130105 Kalaw 130106 Pindaya 130107 Ywarngan 130108 Yatsauk 130109 Pinlaung 130110 Phekon 130151 Kyauktalongyi (Sub-township) 130152 Indaw (Sub-township) 130153 Naungtayar (Sub-township) 130201 Loilem 130202 Le'Char 130203 Nanhsam (South) 130204 Kunhing 130205 Kehsi 130206 Mongkai 130207 Mineshu 130251 Panglong (Sub-township) 130252 Kholan (Sub-township) 130253 Karli (Sub-township) 130254 Minenaung (Sub-township) 130255 Minesan (Monsan) (Sub-township) 130301 Linkhe' 130302 Mone' 130303 Maukme' 130304 Minepan 130351 Homane (Sub-township) 130352 Kengtaung (Sub-township) 130401 Lashio 130402 Theinni 130403 Mineye' 130404 Tantyan 130501 Muse 130502 Namkham 130503 Kukai 130551 Monekoe (Sub-township) 130552 Manhero (Sub-township) 130553 Pansai (Kyukute) (Sub-township) 130554 Tamoenye (Sub-township) 130601 Kyaukme 130602 Naungkhio 130603 Hsipaw 130604 Namtu 130605 Namsan (North) 130606 Momeik 130607 Mabane 130608 Manton 130651 Minengaw (Sub-township) 130652 Minelon (Sub-township) 130701 Kunlon 130801 Laukine 130802 Kongyan 130851 Chinshwehaw (Sub-township) 130852 Mawhtike (Sub-township) 130901 Hopan 130902 Minemaw 130903 Panwine 130952 Panlon (Sub-township) 131001 Makman 131002 Pan San (Pan Kham) 131003 Naphang 131051 Mankan (Sub-township) 131101 Kengtung 131102 Minekat 131103 Mineyan 131104 Minelar 131151 Mine Pauk (Sub-township) 131201 Minesat 131202 Minepyin 131203 Minetung 131251 Minekoke (Sub-township) 131252 Tontar (Sub-township) 131253 Ponparkyin (Sub-township) 131254 Monehta (Sub-township) 131301 Tachileik 131351 Talay (Sub-township) 131352 Kenglat (Sub-township) 131401 Minephyat 131402 Mineyaung 131451 Mineyu (Sub-township) 139999 Shan region, township unknown 140101 Kangyidaunt 140102 Kyaungon 140103 Kyonpyaw 140104 Ngaputaw 140105 Pathein 140106 Yekyi 140107 Thapaung 140151 Ngayokaung (Sub-township) 140152 Hainggyikyun (Sub-township) 140153 Shwethaungyan (Sub-township) 140154 Ngwehsaung (Sub-township) 140155 Ngathaingchaung (Sub-township) 140201 Kyaiklatt 140202 Daydaye 140203 Phyapon 140204 Bogale 140251 Ahmar (Sub-township) 140301 Nyaungdon 140302 Danubyu 140303 Pantanaw 140304 Maubin 140401 Myaungmya 140402 Wakema 140403 Einme 140501 Mawlamyinegyun 140502 Labutta 140551 Pyinsalu (Sub-township) 140601 Kyangin 140602 Zalun 140603 Myanaung 140604 Laymyethna 140605 Hinthada 140606 Ingapu 150101 Tatkon 150102 Zeyarthiri 150103 Ottarathiri 150104 Pobbathiri 150201 Pyinmana 150202 Lewe 150203 Zabuthiri 150204 Dekkhinathiri 159999 Nay Pyi Taw state, district unknown 160415 Thailand 160416 Malaysia 160419 Singapore 160420 China 160421 Japan 160422 South Korea 160423 India 160424 Bangladesh 160425 United States 160428 Other country 999999 NIU (not in universe) Migration: Global Variables -- PERSON Urban or rural previous residence <span class="h2">For all members of the household (1 through 18)</span> <br />[Question 1 through 18 were asked of all persons living in the household.]</p> <p><span class="h3">Place of previous usual residence</span></p> <p><span class="h3">18. Urban or rural</span><div class="i1">[] 1. Urban<br />[] 2. Rural</div> <span class="em">Questions 17 and 18: Place of previous usual residence</span></p> <p>162. Ask "where was [the respondent] previously living before moving to current usual place of residence? This question aims to establish how people have moved within the country. The question intends to capture the last previous place of usual residence. If the place of (last) previous residence is here (here = township of enumeration) write "000". Many persons stay in the same township. If not, write the township 3-digit code or if abroad the country of previous residence using the code list provided. Mark urban or rural in question 19 as appropriate and inquire the same to the respondent whose previous residence is abroad.</p> <p>For persons aged between 00 and 04 years (below 5 years old) the remaining parts of the questionnaire are not applicable hence their information ends here. The remaining questions should be left blank for children below 5 years of age. Myanmar 2014: Persons in conventional households [discrepancies: none] This variable indicates if the person's previous place of residence was urban or rural. 1 Urban 2 Rural 9 NIU (not in universe) Migration: Global Variables -- PERSON Read and write <span class="h2">Age 5 and above (19 through 21)</span> <br />[Question 19 through 21 were asked of persons age 5 and older.]</p> <p><span class="h2">Education (19 through 21)</span></p> <p><span class="h3">19. Can [the respondent] read and write in any language?</span><div class="i1">[] 1. Yes<br />[] 2. No</div> <span class="h3">Education Section </span> <br />Education questions are asked to all persons aged 5 years and above.</p> <p><span class="em">Question 19: Literacy </span></p> <p>163. Ask "can [the respondent] read and write in any language? This is to read and write with understanding. Mark the response as provided by the responses.</p> <div class="i1">[] 1 Yes<br />[] 2 No</div><p>164. It is important to note that some people may have never been to school yet they have learned how to read and write. Others have learned how to read and write through adult education classes (non-formal education system) or similar programs. Yet others might have attended school, but do not know or might have lost how to read or write over time. No literacy test will be administered during the census enumeration. You are required to accept the respondent's self-assessment of reading and writing. If a person can read but not write, mark "2 - no". That is they have to be able to do both (read and write). Same to those who can write, but not read. Writing or reading only a person's name is not sufficient to be regarded as literate. Myanmar 2014: Persons age 5+ in conventional households [discrepancies: none] This variable indicates if the person can read and write. 1 Literate 2 Illiterate 9 NIU (not in universe) Education Variables -- PERSON School attendance <span class="h2">Age 5 and above (19 through 21)</span> <br />[Question 19 through 21 were asked of persons age 5 and older.]</p> <p><span class="h2">Education (19 through 21)</span></p> <p><span class="h3">20. Is [the respondent] currently attending, previously attended or never attended school/college?</span><div class="i1">[] 1. Currently attending<br />[] 2. Previously attended<br />[] 3. Never attended</div> <span class="h3">Education Section </span> <br />Education questions are asked to all persons aged 5 years and above.</p> <p><span class="em">Question 20: School attendance</span></p> <p>165. Ask "is [the respondent] currently attending, previously attended, or has never attended school?" The possible response options are:</p> <div class="i1">[] 1 Currently attending<br />[] 2 Previously attended<br />[] 3 Never attended</div><p>166. School attendance is defined as regular attendance at any regular accredited educational institution or program, public or private, for organized learning at any level of education at the time of the census or, if the census is taken during the vacation period, at the end of the school year or during the last school year. Instruction in particular skills which is not part of the recognized educational structure of the country (for examples, in service training courses employees, training computer skills in colleges) is not considered "educational attendance" for census purposes. Information on school attendance in this census must be collected for all persons aged 5 years and older.</p> <p><span class="pg">[p. 38]</span></p> <p>167. "Regular" school refers to formal education obtained from accredited public, private, religious school, college, university or professional school, whether attendance was full-time or part-time. Regular schooling is that which may advance a person towards a certificate, diploma or professional degree. Schooling other than in regular school should be counted only if the credits obtained are regarded as transferable to a school in regular school system. The language used in the schools is not important, even if it is not Myanmar language but for example English or Chinese. Regular school begins with the first (1st) class at primary level. However, pre-primary school or kindergarten does count as regular school attendance if the age of respondent is 5 years or above. Myanmar 2014: Persons age 5+ in conventional households [discrepancies: none] This variable indicates if the person is attending school. 1 Currently attending 2 Previously attended 3 Never attended 9 NIU (not in universe) Education Variables -- PERSON Highest grade <span class="h2">Age 5 and above (19 through 21)</span> <br />[Question 19 through 21 were asked of persons age 5 and older.]</p> <p><span class="h2">Education (19 through 21)</span></p> <p><span class="h3">21. What is the highest education grade/level [the respondent] _ _ completed?</span><div class="i1">Use the following codes corresponding to the education grade/level:<br /><br />[] 00 None<br />[] 01 - 11 Grade<br />[] 12 College<br />[] 13 Vocational training<br />[] 14 Undergraduate diploma<br />[] 15 Graduate<br />[] 16 Postgraduate diploma<br />[] 17 Masters Degree<br />[] 18 PhD<br />[] 19 Other, specify</div> <span class="h3">Education Section </span> <br />Education questions are asked to all persons aged 5 years and above.</p> <p><span class="em">Question 21: Highest grade/level completed?</span></p> <p>168. Ask "what is the highest education grade/level has [the respondent] completed? The available options are listed below so record appropriately.</p> <div class="i1">[] 00 None<br />[] 01-11 Grade<br />[] 12 College<br />[] 13 Vocational training<br />[] 14 Under grade diploma<br />[] 15 Graduate<br />[] 16 Post graduate diploma<br />[] 17 Master degree<br />[] 18 PhD<br />[] 19 Other</div><p>169. In this question, you will record either the highest education level an individual has completed if a person has previously attended or is attending school. For those attending school, in most cases the education level completed is always not the grade/level they are presently enrolled in, but the previous grade/level. For example, if a child is presently enrolled in grade 6, the highest grade completed will be grade 5, and should be recorded as" 05" on the questionnaire. For children attending first grade write "00".</p> <p>170. Vocational training (record "13") means that completed education/training after high school for certain professions, for example, plumbing, electrical, roofing, refrigeration, carpentry, cabinet making, hair dressing, cosmetology, tailoring etc.</p> <p>171. College "12" means a person is a student at under-graduate university level; Bachelor degrees (Graduate) are coded "15"; all Masters of Arts, Masters of Science and Masters of Philosophy degrees are marked as option "17". Doctorate degree (Ph. D., option "18") is an advanced research university degree, which for successful completion, requires the submission of a thesis or dissertation of publishable quality. For someone who has had no schooling, code "00".</p> <p>172. There are respondents who went to school during different system of education in Myanmar. That is during the colonial period, in the former education system and the current education system. A table has been prepared and presented below to assist in coding of education attainment question. It will also be given to interviewers during field enumeration. If for example, a respondent tells you that he completed Standard 9 during former education system, check the correct code using the conversion table, according to the first column and last column the correct code is "10". The conversion table will prove very useful for those respondents who went through the pre-colonial and former system of education. It should also be used for foreigners who schooled in different education systems. Those who have completed education level i.e. high school - "11", diploma - "14", university - "15", should be coded appropriately. Myanmar 2014: Persons age 5+ [discrepancies: none] This variable indicates the highest educational level or grade the person has completed. 00 None 01 Grade 1 02 Grade 2 03 Grade 3 04 Grade 4 05 Grade 5 06 Grade 6 07 Grade 7 08 Grade 8 09 Grade 9 10 Grade 10 11 Grade 11 12 College 13 Vocational training 14 Undergraduate diploma 15 Graduate 16 Postgraduate diploma 17 Master degree 18 Ph.D. 19 Other 99 NIU (not in universe) Education Variables -- PERSON Activity status <span class="h2">Age 10 and above (22 through 24)</span> <br />[Questions 22 through 24 were asked only of persons age 10 and older.</p> <p><span class="h2">Labor force (22 through 24)</span></p> <p><span class="h2">Activity status</span></p> <p><span class="h3">22. What was [the respondent's] activity status during the last 12 months? (April 2013 - March 2014)</span><div class="i1">If options 6 to 11 skip to Q25<br /><br />[] 1. Employee (Government)<br />[] 2. Employee (Private, Org)<br />[] 3. Employer<br />[] 4. Own account worker<br />[] 5. Contributing family worker<br />[] 6. Sought work<br />[] 7. Did not seek work<br />[] 8. Full time student<br />[] 9. Household work<br />[] 10. Pensioner, retired, elderly person<br />[] 11. Ill, disabled<br />[] 12. Other</div> <span class="h3">Labor force section </span> <br />The Labor Force section is applicable to all persons 10 years and above. For respondents age below 10 years you will skip the section, leave it blank.</p> <p><span class="em">Question 22: Main activity status during the last 12 months</span></p> <p>173. Ask "what was [the respondent]'s main activity status during the last 12 months before the Census (April 2013 to March 2014)? What the respondent was doing denotes the work, economic activity or employment that occupied most of the respondent's time during the last 12 months. Here 'employment' is interpreted as work for at least one hour daily in the reference period. Economic activity is work that leads to production of goods and service. The possible response options are as follows.</p> <p><span class="pg">[p. 40]</span></p> <p>174. Employed (worked for at least 1 hour for pay, profit or family gain or was temporarily absent from work but had a job, farm or business. Note that very little paid work is needed to be classified as 'employed'.</p> <div class="i1">1. Employee working for the government. All people working in the government of Myanmar or any other should fall under this option.<br /><br />2. Employee (working for private employer or private organization for pay in cash or in kind). This category comprises persons who during the reference period worked for wages, salaries, commissions, tips, contracts or payment in kind (especially in the rural areas where people who have rendered services may be paid using food or clothing). All people in NGOs, international organizations, companies, etc. must be coded here.<br /><br />3. Employer (employing one or more employees). This category comprises persons who during the reference period worked in their own business, which also employs other persons. The person must have also been spending much of his/her time at the place of work than in other work. This is to say that if the person has two places of work then this is where he/she spends more of the working time. The people employed can be paid either in cash or in-kind.<br /><br />4. Own-account worker (not employing any employee). This category comprises self-employed persons who worked on own business or worked on own/ family business for family gain. This category can include, for example, artisans, self-employed mechanics, traders in farm produce and family workers offering services in own or family business. Any member of the household working on the family holding for pay will fall under code "2".<br /><br />5. Contributing family worker (working without pay in the business or farm of another household/family member)</div><p>175. Not employed, available for work</p> <div class="i1">6. Sought work: A person who in the reference period was actively looking for work belongs to this category "6". This category should not include the under-employed (i.e. those who have paid work but wish to leave for better opportunities). Persons who have no work at all and are looking for work will fall under this category. If a person is working on the family holding but is seeking work, he/she should be coded as "contributing family worker" and not as "seeking work". This category should include only persons who are available full-time for work and hence are actively looking.<br /><br />7. Not seeking work: This person is not working nor looking for work because he/she is discouraged, but would usually take up a job when offered one.</div><p>176. Not employed, not available for work</p> <div class="i1">8. Unemployed student: This is a person who spent most of his/her time in a regular educational institution (primary, secondary, college, university etc.) and hence not available for work. If, for instance, a student was part-time during the better part of the reference period and was engaged in gainful employment, he/she should be coded as employed. This may be the case amongst the university students.<br /><br />9. Household work (homemaker): Is a person of either sex involved in household chores in his/her own home e.g. fetching water, cooking, babysitting, etc., who did not work for pay or profit or sought work. These categories should not include houseboys/girls who fall under category "2". If such a person worked on family holding without pay they should be coded as "5" and not as "9". Please probe. Many women, especially in rural areas, consider themselves as housewives, but work in the fields on the family farms. They should be classified as "5" Contributing family workers.<br /><br />10. Pensioner, retired, elderly person: This is a person who reports that during the 12 months, he/she was not engaged in any economic activity because he/she had retired either due to age, sickness, or voluntarily. If a person has retired, but is doing some work/business, he/she should be coded as "2", "3", "4" or "5" as appropriate. If he/she has retired, but is seeking work he/she should be coded as "6".<br /><br />11. Disabled or ill: This is somebody who cannot work due to some form of disability or illness. Do not assume that all disabled persons cannot work. For example, a blind person who is in wage employment will fall under category "2" and not "11". Similarly physically disabled person working on the family holding should fall under category "2" or "5". You should probe if you are unsure at first.<br /><br />12. Other: This category includes any other persons not mentioned above. You are to probe to find out whether unpaid family workers consider themselves as "seeking work", etc. and code them accordingly. For example, if a young man helps his uncle to sell goods in a shop without receiving pay, probe whether he is seeking work, and if so code him as such. In such case code 5 would be appropriate. In such case the person is either working without pay (code 5) or employed with pay (code 2).</div><p>This question is aimed at identifying the size of the labor force and the reasons why people are not working. It is therefore important this question is asked with all the care. In most cases, women may assume that they are not working but they are deeply involved in the workforce. Below are some photos which should probe you to inquire if the people both women and men say that they are not working; ask them what they are doing then code as appropriate. Myanmar 2014: Persons age 10+ [discrepancies: none] This variable indicates the activity status of the person during the last 12 months (April 2013 through March 2014). 01 Employee (government) 02 Employee (private, organization) 03 Employer 04 Own account worker 05 Contributing family worker 06 Sought work 07 Did not seek work 08 Full time student 09 Household work 10 Pensioner, retired, elderly person 11 Ill or disabled 12 Other 99 NIU (not in universe) Work Variables -- PERSON Occupation <span class="h2">Age 10 and above (22 through 24)</span> <br />[Questions 22 through 24 were asked only of persons age 10 and older.</p> <p><span class="h2">Labor force (22 through 24)</span></p> <p><span class="h3">Occupation</span></p> <p>23. What work was [the respondent] mainly doing during the last 12 months? ____</p> <div class="i1">Write detailed work descriptions (e.g. Primary teacher, rice farmer, taxi driver)</div> <span class="h3">Labor force section </span> <br />The Labor Force section is applicable to all persons 10 years and above. For respondents age below 10 years you will skip the section, leave it blank.</p> <p><span class="em">Question 23: Occupation</span> <br />177. Ask "what work was [the respondent] mainly doing during the last 12 months before the census?" This question must be asked of all people who coded "1" to "5" in Question 22.</p> <p><span class="pg">[p. 42]</span></p> <p>178. Occupation is the kind of work done during the last 12 months by the person employed, regardless of the industry or status in employment of the person. Write detailed description of the work being done such as accounts clerk, legal secretary, domestic worker, fisherman, human resource manager, etc. The writing should be done in space provided in Myanmar language.</p> <p>179. State the person's occupation in his/her main job during the reference year and the type of work done. Main job is that economic activity where the person spends most of the time working than any other work. Be sure to obtain a description of their main tasks/duties since often times a job title does not sufficiently describe the occupation for the purpose of coding. For example occupations such as "clerk," "engineer," "manager", "seaman," "supervisor," "teacher" etc. are too vague. You will need to probe for a more detailed answer. Examples of various occupations are provided below.</p> <p>180. Your job is to write a legible and concise description of the respondent's occupation. Errors in the coding of occupations could occur if you do not give adequate or complete descriptions of tasks and duties performed by the respondent. Each employed person who is recorded 1-5 in Q22 must have occupation in Q23. Myanmar 2014: Employed persons age 10+ in conventional households [discrepancies: type I none; type II 0.1%] This variable indicates the person's main occupation during the last 12 months. 11 Chief executive senior officials and legislators 12 Administrative and commercial managers 13 Production and specialized services managers 14 Hospitality, retail and other services managers 21 Science and engineering professionals 22 Health professionals 23 Teaching professionals 24 Business and administrative professionals 25 Information and communications technology professionals 26 Legal, social and cultural professionals 31 Science and engineering associate professionals 32 Health associate professionals 33 Business and administrative associate professionals 34 Legal, social and cultural and related associate professionals 35 Information and communications technicians 41 General and keyboard clerks 42 Customer services clerks 43 Numerical and material recording clerks 44 Other clerical support workers 51 Personal service workers 52 Sales workers 53 Personal care workers 54 Protective services workers 61 Market-oriented skilled agricultural workers 62 Market-oriented skilled forestry, fishery and hunting workers 63 Subsistence farmers, fishers, hunters and gatherers 71 Building and related trades workers, excluding electricians 72 Metal, machinery and related trades workers 73 Handicraft and printing workers 74 Electrical and electronic trades workers 75 Food processing, wood working, garment and other craft and related trades workers 81 Stationary plant and machine operators 82 Assemblers 83 Drivers and mobile plant operators 91 Cleaners and helpers 92 Agricultural forestry and fishery labourers 93 Labourers in mining, construction, manufacturing and transport 94 Food preparation assistants 95 Street and related sales and service workers 96 Refuse workers and other elementary workers 98 Unknown 99 NIU (not in universe) Work: Occupation Variables -- PERSON Industry <span class="h2">Age 10 and above (22 through 24)</span> <br />[Questions 22 through 24 were asked only of persons age 10 and older.</p> <p><span class="h2">Labor force (22 through 24)</span></p> <p>24. What is the major product or service provided in the organization/enterprise where [the respondent] mainly worked during the last 12 months? ____ </p> <div class="i1">Write detailed descriptions (e.g. Hotel service, building construction, garment manufacture)</div> <span class="h3">Labor force section </span> <br />The Labor Force section is applicable to all persons 10 years and above. For respondents age below 10 years you will skip the section, leave it blank.</p> <p><span class="em">Question 24: Industry</span></p> <p>181. Ask "what is the major product or service produced in the organization/enterprise where [the respondent] mainly worked during the last 12 months?"</p> <p>182. Industry is the branch of economic activity carried out at the person's place of work. This is defined in terms of the kind of goods produced or services supplied by the enterprise in which the person works and NOT necessarily the specific duties or functions of the person's job. For example, in the case of a contract cook working in a canteen in a factory that makes television sets? The industry should be manufacture of electrical goods. But her occupation is a cook at worker place. Using such examples you would record construction/electrical installation, baking of bread, repair of boats/yacht, activities of trust company or retail banking, etc. There are cases where some people may also inform you that they are engaged in illegal activities like stealing, prostitution, you will have to record this as well. Your role is to get the correct information, write it down then coding will be done in the office in Naypyitaw.</p> <p>183. For the corresponding main occupation in question 23 indicate the name of the business carried out by the employer. If it is not obvious from the name, or the business has no name, you should clearly indicate what the employer makes or does. Some employers are engaged in more than one industry (e.g. Government) therefore it is important to specify the type of industry that relates to the person for whom you are recording information. Write the name of the business or the department in government. Examples of various industries are provided below. Probe to find out the name of the business and the main type of activities carried out there.</p> <p><span class="pg">[p. 43]</span></p> <p>184. Your job is to write a legible and concise description of the type of business carried out where the person works. Errors in the classification of industries could occur when you do not give adequate or complete descriptions of the type of business. For example, inaccuracies may arise if you describe the business of an establishment by the occupation of the person employed there rather than the activity that is carried out within the business. Myanmar 2014: Employed persons age 10+ in conventional households [discrepancies: type I none; type II 0.1%] This variable indicates the industry of the establishment or sector in which the person worked during the last 12 months. 001 Crop and animal production, hunting and related service activities 002 Forestry and logging 003 Fishing and aquaculture 005 Mining of coal and lignite 006 Extraction of crude petroleum and natural gas 007 Mining of metal ores 008 Other mining and quarrying 009 Mining support service activities 010 Manufacture of food products 011 Manufacture of beverages 012 Manufacture of tobacco products 013 Manufacture of textiles 014 Manufacture of wearing apparel 015 Manufacture of leather and related products 016 Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials 017 Manufacture of paper and paper products 018 Printing and reproduction of recorded media 019 Manufacture of coke and refined petroleum products 020 Manufacture of chemicals and chemical products 021 Manufacture of basic pharmaceutical products and pharmaceutical preparations 022 Manufacture of rubber and plastics products 023 Manufacture of other non-metallic mineral products 024 Manufacture of basic metals 025 Manufacture of fabricated metal products, except machinery and equipment 026 Manufacture of computer, electronic and optical products 027 Manufacture of electrical equipment 028 Manufacture of machinery and equipment n.e.c. 029 Manufacture of motor vehicles, trailers and semi-trailers 030 Manufacture of other transport equipment 031 Manufacture of furniture 032 Other manufacturing 033 Repair and installation of machinery and equipment 034 Making jewelry 035 Electricity, gas, steam and air conditioning supply 036 Water collection, treatment and supply 039 Sewerage, waste collection, remediation activities, and other waste management services 041 Construction of buildings 042 Civil engineering 043 Specialized construction activities 045 Wholesale and retail trade and repair of motor vehicles and motorcycles 046 Wholesale trade, except of motor vehicles and motorcycles 047 Retail trade, except of motor vehicles and motorcycles 049 Land transport and transport via pipelines 050 Water transport 051 Air transport 052 Warehousing and support activities for transportation 055 Accommodation 056 Food and beverage service activities 058 Publishing activities 059 Motion picture, video and television programme production, sound recording and music publishing activities 060 Programming and broadcasting activities 061 Telecommunications 062 Computer programming, consultancy and related activities 063 Information service activities 064 Financial service activities, except insurance and pension funding 065 Insurance, reinsurance and pension funding, except compulsory social security 066 Activities auxiliary to financial service and insurance activities 068 Real estate activities 069 Legal and accounting activities 071 Architectural and engineering activities; technical testing and analysis 073 Advertising and market research 074 Other professional, scientific and technical activities 075 Veterinary activities 077 Rental and leasing activities 079 Travel agency, tour operator, reservation service and related activities 080 Security and investigation activities 081 Services to buildings and landscape activities 082 Office administrative, office support and other business support activities 084 Public administration and defense; compulsory social security 085 Education 086 Human health activities 087 Residential care activities 088 Social work activities without accommodation 090 Creative, arts and entertainment activities 091 Libraries, archives, museums and other cultural activities 092 Gambling and betting activities 093 Sports activities and amusement and recreation activities 094 Activities of membership organizations 095 Repair of computers and personal and household goods 096 Other personal service activities 097 Activities of households as employers of domestic personnel 098 Undifferentiated goods- and services-producing activities of private households for own use 099 Activities of extraterritorial organizations and bodies 998 Unknown 999 NIU (not in universe) Work: Industry Variables -- PERSON Male children born <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">25. Number of children ever born alive</span><div class="i1">If no children, write "00".<br /><br />_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes.</p> <p><span class="em">Question 25: Number of children ever born alive</span> <br />188. Ask each ever-married woman age 15 years and above "how many children has [the respondent] ever given birth alive?" How many males and females?</p> <p>189. Live births include even those births where the child lives for only a short time. Twins count as one live birth. But this question records the number of children, so twins will be recorded as two children. Live births do not include stillbirths, that is, children who were born dead and therefore did not show any sign(s) of life at the time of birth. The census is concerned only with children born alive. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of male children born to a woman. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Female children born <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">25. Number of children ever born alive</span><div class="i1">If no children, write "00".<br /><br />_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes.</p> <p><span class="em">Question 25: Number of children ever born alive</span> <br />188. Ask each ever-married woman age 15 years and above "how many children has [the respondent] ever given birth alive?" How many males and females?</p> <p>189. Live births include even those births where the child lives for only a short time. Twins count as one live birth. But this question records the number of children, so twins will be recorded as two children. Live births do not include stillbirths, that is, children who were born dead and therefore did not show any sign(s) of life at the time of birth. The census is concerned only with children born alive. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of female children born to a woman. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Male children in household <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">26. How many of those children are living in this household?</span><div class="i1">_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of male children born to a woman who are living in the household at the time of the census. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Female children in household <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">26. How many of those children are living in this household?</span><div class="i1">_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of female children born to a woman who are living in the household at the time of the census. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Male children living elsewhere <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">27. How many of those children are living elsewhere (not in this household)?</span><div class="i1">_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of male children born to a woman who are living elsewhere (not in the household) at the time of the census. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Female children living elsewhere <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">27. How many of those children are living elsewhere (not in this household)?</span><div class="i1">_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of female children born to a woman who are living elsewhere (not in the household) at the time of the census. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Male children dead <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">28. How many of those children are no longer alive (dead)?</span><div class="i1">_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of male children born to a woman who are no longer alive. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Female children dead <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">28. How many of those children are no longer alive (dead)?</span><div class="i1">_ _ Male<br />_ _ Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15+ in conventional households [discrepancies: none] This variable indicates the number of female children born to a woman who are no longer alive. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of last live birth <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">29. Date of last live birth </span><div class="i1">_ _ Month<br />_ _ _ _ Year</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15-59 in conventional households who ever had a live birth [discrepancies: none] This variable indicates the month of birth of the last child born by the respondent. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of last live birth <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">29. Date of last live birth </span><div class="i1">_ _ Month<br />_ _ _ _ Year</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15-59 in conventional households who ever had a live birth [discrepancies: none] This variable indicates the year of birth of the last child born by the respondent. 1970 1969 or 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Sex of last live birth <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">30. Sex of last live birth</span><div class="i1">[] 1. Male<br />[] 2. Female</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15-59 in conventional households who ever had a live birth [discrepancies: type I trace; type II 0.2% ] This variable indicates the sex of the last live birth a woman had. 1 Male 2 Female 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Last child born still alive <span class="h2">Ever married women (aged 15 and above) (25 through 31)</span> <br />[Question 25 through 31 were only asked of ever married women age 15 and older.]</p> <p><span class="h3">31. Is the child still alive?</span><div class="i1">[] 1. Yes<br />[] 2. No</div> <span class="h3">Births to Ever Married Women Section (Fertility)</span></p> <p>186. The questions on births and children related issues will be asked to ever-married women aged 15 and above. Many women may be reluctant to answer questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness, tact, understanding and, for some questions such as death, sympathy.</p> <p>187. Only females above 15 years who have ever married should respond to the questions on births. Use Q4 - sex, Q5 - age, and Q6 - marital status, to determine eligible persons for this section. These questions will be used to estimate fertility and childhood mortality levels in Myanmar. The information would also be used to undertake population projections required for future planning purposes. Myanmar 2014: Ever-married women age 15-59 in conventional households who ever had a live birth [discrepancies: type I 0.2%; type II 0.2% ] This variable indicates if the last live birth a woman had is still alive. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Person weight Myanmar 2014: All persons This variable indicates the person's sample weight. This is a 6-digit numeric variable with 4 implied decimal places Technical Person Variables -- PERSON